Data Processing

Data Processing Developer Jobs

784 jobs found

Today

Application Developer II

BioBridge Global San Antonio, TX

San Antonio, TX

Today

$89k - $113k/yr Full time .NET .NET Core Angular

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Job Description

Context: BioBridge Global is hiring an Application Developer II to design, develop, enhance, and support applications used across the organization.

Responsibilities

Work with and mentor a team of Application Developers to achieve software project and maintenance goals
Design, enhance, and implement new and existing software applications
Serve as a SME for multiple standard organizational platforms
Design UI mock-ups and translate them to ReactJS front-end
Make design and technical decisions for ReactJS projects
Develop application code and unit tests using ReactJS, API, RESTful services
Troubleshoot and resolve application issues
Research and evaluate new application technologies
Be directly involved in at least two of the following: Microsoft .NETCore, C#, SharePoint, Cloud Development, SQL Server, Oracle, workflow, and other application development technologies
Design, prepare, and execute coded unit tests using MS Visual Studio testing tools
Mentor junior-level Developers and review developed applications for quality and development standardization
Maintain development standards for team projects in GitHub
Attend and participate in staff meetings and related activities; attend training to stay current on Application Development advancements
Meet with internal customers to gather requirements and define scope of work and deliverables
Oversee installation and maintenance of all software applications
Provide technical strategy and best-practice direction to employees and coworkers
Communicate with other departments regarding application issues
Oversee management of mission critical applications to ensure availability
Maintain a close working relationship with departmental management and coworkers
Perform other duties and responsibilities as required or assigned
Assist in other laboratory areas as directed

Requirements

Education: high school diploma or general equivalency diploma
Experience: 5 or more years of Applications Developer experience
Programming: object-oriented programming experience; C# preferred
SQL: SQL experience; T-SQL and PL/SQL preferred
Web application development: extensive experience using ReactJS, HTML5/CSS3, jQuery to develop applications quickly and effectively
Source control: experience with Team Foundation Server and GitHub preferred
Technology preferences: prefer experience with 4 or more of the following: .NET, MVC, Web API, Web Application Development, C#, SQL Server, Entity Framework, AngularJS, JavaScript, HTML5/CSS3
Graphic editing preference: experience with Adobe Photoshop, InDesign, or Illustrator
Regulatory/quality: obtain working knowledge of regulatory/quality requirements; follow all SOPs and policies
Regulatory understanding: understanding of regulatory requirements in a technology-related industry
Business process: knowledge of business process analysis and industry/functional best practices
Interpersonal/problem solving: excellent interpersonal and problem solving skills
Confidentiality: ability to keep information confidential
Professional conduct: neat appearance and well groomed
Work style: self-starter, self-directed, professional, detail oriented, self motivated, innovative, creative, assertive, organized, communicative, able to work independently
Planning: anticipate future application development needs to improve and update current systems
Driving: valid United States Driver’s License; able to drive on behalf of the organization
Motor vehicle operation: capable of operating motor vehicles in all types of weather conditions

Licenses and Certifications

Certified MT (CLS) or equivalent preferred
SBB required for AABB IRL Accreditation
US Passport preferred
Valid United States Driver’s License

Technologies

ReactJS (ReactJS front-end), API, RESTful services
Microsoft .NETCore, C#, SharePoint, Cloud Development
SQL Server, Oracle, workflow
MS Visual Studio testing tools
GitHub, Team Foundation Server
HTML5, CSS3, jQuery
T-SQL, PL/SQL
.NET, MVC, Web API, Web Application Development, Entity Framework
AngularJS, JavaScript
Adobe Photoshop, InDesign, Illustrator

Working Environment and Travel Requirements

Office environment: well-lighted, air conditioned, and heated
Exposure: may be exposed to electrical and chemical hazards and other conditions common to an office environment
Schedule: may be required to work any time of day, evening, or night during the week or weekend, including on-call
Occupational Exposure Assignment: Category II

Physical Requirements

Will sit, stand, walk, and bend during working hours
Drive on behalf of the organization
Reach, lift, and carry up to 50 lbs
Manual and finger dexterity and eye-hand coordination
Normal or corrected vision and hearing corrected to a normal range

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Today

Data Engineer, GCS Data Science

Google New York, NY

New York, NY

Today

$106k - $151k/yr Full time Backend Developer Analytics Artificial Intelligence

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Job Description

On Google’s GCS Data Science team, this Data Engineer role focuses on turning complex business data into reliable pipelines and usable insights. You will help build scalable ETL workflows and reporting automation that support feature engineering and the development and scaling of ML and AI models.

Working onsite in New York, NY, you’ll operate in an agile environment alongside data scientists and stakeholders across the organization. The Data Science Engineering (DSet) subteam supports the broader GCS Data Science effort through new data pipelines, automation, observability, and reporting tooling for GCS initiatives.

What you’ll do

Build data pipelines, reports, best practices, and frameworks that enable analysts and other organizational stakeholders.
Apply feature engineering practices to meet data needs for ML and AI model development, including ETL pipeline development to support downstream scaling.
Ensure pipeline quality by adopting best practices for data integrity, test design, analysis, validation, and documentation.
Design and develop scalable, actionable solutions such as dashboards, automated collateral, and web applications that communicate insights.
Collaborate with stakeholders to identify feature and tooling gaps and innovate on behalf of customers.

What you’ll bring

Bachelor’s degree in Computer Science or a related technical field, or equivalent practical experience.
At least 1 year of experience designing data pipelines (ETL) and model data.
Experience analyzing data and creating reports, including database query (for example, SQL) and visualization tools (for example, Tableau and dashboards).
Experience with one or more general-purpose programming languages, such as Python, C/C++, or Java.

Technologies

ETL, ML/AI, SQL, Tableau, dashboards
Python, C/C++, Java

About the role

The GCS Data Science team addresses challenging problems within Google Customer Solutions (GCS) for the Global Business Organization (GBO). The team’s objective is to build efficient and scalable ML models that help small and midsize businesses grow using Google solutions.

Compensation and benefits

USD 106,000 - 151,000 per year
15% bonus target
equity
benefits
Health insurance
401k match

Preferred qualifications

Experience working in a data science environment supporting feature engineering and model automation needs.
Experience with big data tools, distributed computing, and non-relational databases.
Structured problem-solving skills, including the ability to break down ambiguous problems and propose impactful data modeling designs.
Strong interest in analyzing large and complex datasets and translating them into information that supports business decisions.

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Today

Senior IT Data Engineer

System One Washington, DC

Washington, DC

Today

Contract Senior Apache Airflow AWS

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Job Description

System One is hiring a Senior IT Data Engineer to support the Federal Reserve Board’s Division of Research & Statistics (R&S) DATA section in Washington, DC (onsite).

Responsibilities

Expand and optimize data and data pipeline architecture.
Optimize data flow and collection to support economic policy and research teams.
Design and develop optimal data delivery architecture.
Improve existing data systems and/or build new systems from the ground up.
Optimize or redesign the R&S division data architecture to support next generation data initiatives.
Support economists and technical experts.
Provide service-minded support for multiple teams and systems with a self-directed working approach.
Design and communicate enterprise information architecture across conceptual, logical, and physical levels.

Requirements

Bachelor’s degree in computer science, Information Technology, Engineering, or related technical field; at least 7 years of related experience (advanced degree preferred).
Advanced working knowledge of SQL.
Experience with relational database platforms including PostgreSQL, Microsoft SQL Server, and MySQL.
Advanced working knowledge of Python, R, and other scripting languages used for data engineering and analytics.
Experience with large-scale data systems: distributed computing, scalable data processing, data storage architecture, and optimization of high-volume data workloads.
Experience designing, developing, and automating ETL/ELT workflows and data integration pipelines.
Experience building, optimizing, and maintaining scalable databases, data pipelines, and data processing frameworks.
Experience with workflow orchestration and pipeline automation tools such as Apache Airflow, Prefect, Dagster, or AWS Step Functions.
Experience migrating workflows and data pipelines between on-premises and cloud environments.
Experience processing, analyzing, and integrating structured and unstructured data sources.
Experience developing in Linux and using source control platforms such as GitLab and/or GitHub.
Ability to perform root cause analysis on internal and external data and business processes to answer business questions and identify improvement opportunities.
Ability to design and communicate enterprise information architecture at conceptual, logical, and physical levels.
In-depth experience designing and implementing database, data lake, and enterprise data platform solutions.
Strong hands-on software engineering experience including development, testing, and deployment of data applications and services.
Excellent oral and written communication skills, with a strong customer service orientation.
Exceptional analytical, problem-solving, and troubleshooting skills.
Understanding of time series data and related analytical and forecasting techniques.
Experience working in a research environment and/or with economic or financial data.
Experience with NoSQL and graph database technologies.
Experience developing, training, deploying, and maintaining machine learning models.
Working experience with AWS, Microsoft Azure, and Snowflake.
Experience implementing data warehouses utilizing Change Data Capture (CDC) methodologies.
Experience implementing and maintaining CI/CD pipelines and DataOps platforms.
Working knowledge of additional programming and scripting languages such as Java, Scala, JavaScript, or Perl.

Technology Stack

SQL, PostgreSQL, Microsoft SQL Server, MySQL
Python, R
Apache Airflow, Prefect, Dagster, AWS Step Functions
Linux, GitLab, GitHub
NoSQL, graph database technologies
Machine learning models
AWS, Microsoft Azure, Snowflake
Change Data Capture (CDC)
CI/CD pipelines, DataOps
Java, Scala, JavaScript, Perl

Benefits

Eligible employees health and welfare benefits coverage options including medical, dental, vision, spending accounts, life insurance, voluntary plans.
Participation in a 401(k) plan.

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Today

Data Engineer, Specialist Technology Team (STT), Centralized Data & Analytics

Amazon Web Services, Inc. New York, NY

New York, NY

Today

$132k - $197k/yr Full time Amazon Athena Amazon Emr Amazon Web Services

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Job Description

AWS Specialist Technology Team (STT) is seeking a Data Engineer to help create a centralized analytics data platform from the ground up. This role focuses on scalable ETL/ELT, data modeling, and operational ownership to unify telemetry, usage metrics, and business outcomes for agent-driven analytics and executive decision-making.

Responsibilities

Design, build, and operate scalable ETL/ELT pipelines that ingest product telemetry, usage events, and business outcome data from multiple heterogeneous sources across the STT product portfolio
Architect and implement a centralized data platform using AWS-native services including Redshift, S3, Glue, Lake Formation, Lambda, and Athena to establish a single source of truth for organizational analytics
Build and maintain data models that connect product usage signals to business outcomes, including pipelines that relate engagement and progression to revenue impact
Develop data infrastructure for AI/ML pipelines and agentic systems, including MCP tools and natural-language data access layers
Implement data quality frameworks with automated monitoring, alerting, and validation to maintain accuracy and reliability as the platform scales
Create self-service data products with defined SLAs, documentation, and governance to reduce ad-hoc requests and enable stakeholders to answer their own questions
Collaborate with Applied Scientists and SDE teams to deliver clean, well-modeled datasets for agent evaluation frameworks, retrieval quality measurement, and content effectiveness scoring
Establish data contracts, lineage tracking, and catalog metadata to improve discoverability and organizational trust
Maintain operational excellence by owning on-call responsibilities, monitoring pipeline health, and resolving data freshness or quality issues before they affect consumers
Support the transition from static dashboards to agentic data systems by building foundational data layers that AI agents query and reason over

Requirements

3+ years of data engineering experience
3+ years of experience developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes
3+ years of experience developing and operating large-scale data structures for business intelligence analytics using SQL
3+ years of experience developing and operating large-scale data structures for business intelligence analytics using data modeling
3+ years of experience in the job offered or a related occupation

Technologies

Redshift, S3, Glue, Lake Formation, Lambda, Athena
ETL, ELT
SQL
EMR, Kinesis, FireHose
IAM roles and permissions
Natural-language data access layers
MCP tools

Benefits

Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
401(k) matching
Paid time off
Parental leave
Sign-on payments
Restricted stock units (RSUs)

Preferred Qualifications

Experience with AWS technologies such as Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
Experience with non-relational databases and data stores, including object storage, document or key-value stores, graph databases, and column-family databases

About the Team

Join a high-growth engineering organization applying generative AI and agentic technologies to transform how AWS field teams operate
The centralized analytics team is being built from the ground up, and you will be one of the first two Data Engineers on the team
Work alongside Business Intelligence Engineers, a Senior BD, an Applied Scientist, and a TPM
Make foundational architectural decisions that shape how the platform will be built, scaled, and operated for years to come
Operate in an environment where innovation is fast, problems are ambiguous, and impact is measured across thousands of field team members and the customers they serve
Help define how an entire organization consumes and acts on data through foundational platform architecture

Role Details

Location: New York, NY (onsite)
Compensation: USD 132,100 - 196,600 per year

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Today

Machine Learning Engineer

Goliath Partners San Francisco, CA

San Francisco, CA

Today

$250k - $250k/yr Full time Ai Ml Artificial Intelligence Data Analysis

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Job Description

As a Machine Learning Engineer at Goliath Partners, an early-stage AI fintech startup, you will design and ship production‑grade ML models, construct data pipelines and real-time decisioning APIs, and own projects from initial research through deployment. This onsite role is based in San Francisco, CA.

Compensation

Salary: USD 250,000 - 250,000 per yearly

Responsibilities

Design and scale machine learning models focused on affordability, risk assessment, and predictive analytics.
Develop data pipelines and APIs to bring ML capabilities into production at scale.
Collaborate with product, data, and engineering teams to deliver customer-facing features.
Experiment with diverse approaches and make informed decisions on when to apply ML versus alternative methods.
Drive ongoing improvements in model performance, monitoring, and reliability.

Requirements

Strong product mindset with a passion for solving real customer problems.
Hands-on ML engineer capable of end-to-end work from research to production data pipelines.
Proficiency in Python, modern ML frameworks, and distributed systems.
High-quality standards while maintaining velocity and iterative delivery.
Interest in operating within a high-ownership, early-stage startup environment.

Technologies

Python

What you'll do

Develop and scale ML models for affordability, risk, and predictive analytics.
Build data pipelines and APIs that enable production-grade ML at scale.
Work with product, data, and engineering teams to ship features for customers.
Assess multiple approaches and apply ML where advantageous, selecting alternatives when appropriate.
Enhance model performance, monitoring, and reliability through robust practices.

Who you are

Strong product mindset with a passion for solving real customer problems.
Hands-on ML engineer comfortable with end-to-end responsibilities (research, data pipelines, production).
Experienced in Python, modern ML frameworks, and distributed systems.
Commitment to high-quality work while delivering quickly and iteratively.
Motivation to operate in a high-ownership, early-stage startup environment.

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Today

Senior Machine Learning Engineer

Siemens Raleigh, NC

Raleigh, NC

Today

Full time Senior AI Ai Ml

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Job Description

Siemens invites a Senior Machine Learning Engineer to drive LLM driven applications on AWS, overseeing production‑grade ML and LLM services and owning the complete model lifecycle with modern MLOps practices. This onsite role is based in Raleigh, North Carolina.

Responsibilities

Build LLM applications by designing and implementing retrieval augmented generation pipelines, prompt orchestration, tools and agents, safety guardrails, and evaluation harnesses; instrument for latency, cost, and quality.
Own the ML lifecycle from data curation and feature engineering through training and fine‑tuning (LoRA/QLoRA), A/B testing, deployment, monitoring, and ongoing improvement of models and prompts.
Productionize on AWS by shipping scalable services on EKS, ECS, and Lambda; leverage SageMaker, Bedrock, EMR, MSK, and Step Functions; implement observability via CloudWatch and OpenTelemetry and apply cost controls.
Lead MLOps and governance efforts by establishing CI/CD for models (MLflow, Kedro, SageMaker Pipelines), model/version registries, data and prompt lineage, evaluation gates, and responsible‑AI controls.
Collaborate with Brightly stakeholders to translate asset‑management use cases into ML/LLM solutions, working with product managers and UX to deliver customer‑facing features that improve reliability, safety, and sustainability.
Perform exploratory data analysis on structured, semi‑structured, and unstructured data to uncover patterns, correlations, feature importance, and data quality concerns.
Conduct in‑depth research on asset‑related, operational, and domain datasets to identify root causes, trends, and predictive signals.
Operate in a pragmatic, product‑oriented manner, focusing on measurable outcomes and rapid iteration with stakeholders.
Demonstrate engineering excellence by delivering production‑quality Python, designing reliable APIs and services, and upholding testing and observability standards.
Provide collaborative leadership by mentoring peers and influencing architectural decisions across teams.

Requirements

8–10 years of total software or ML engineering experience, including 2+ years building and operating ML systems in production.
1+ year hands‑on experience developing LLM applications (RAG, fine‑tuning, prompt engineering, evaluators/guardrails, agentic workflows) using Langchain and Langgraph.
AWS proficiency (3+ years) with core services (EKS/ECS, Lambda, S3, DynamoDB or RDS, Step Functions, IAM) and ML stack (SageMaker, Bedrock or HF on AWS).
Modeling and frameworks: Python, PyTorch, Hugging Face ecosystem; experience with vector stores (OpenSearch, PGVector, Pinecone), embeddings, retrieval, and NLP/LLM evaluation metrics.
MLOps: CI/CD for ML, model registries, experiment tracking, telemetry/monitoring, automated retraining; Docker/Kubernetes; GitHub Actions or GitLab CI.
Data engineering fluency: ETL/ELT, streaming and batch processing (Spark/Flink), and data quality and governance controls for ML.
Education: Bachelor’s degree required, Master’s degree preferred.

Technologies

Python
PyTorch
Hugging Face ecosystem
Langchain, Langgraph
AWS (SageMaker, Bedrock, EKS, ECS, Lambda, S3, DynamoDB, RDS, Step Functions, EMR, MSK)
OpenSearch, PGVector, Pinecone
Spark, Flink
Cloud monitoring: CloudWatch, OpenTelemetry
Docker, Kubernetes
GitHub Actions, GitLab CI
MLflow, Kedro, SageMaker Pipelines

Nice to Have

Experience with distributed training (FSDP, DeepSpeed), RLHF, or Inferentia/Trainium optimization.
Exposure to sustainability, asset management, or intelligent operations domains.
Familiarity with security and regulatory compliance considerations for ML systems in enterprise environments.

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Machine Learning Engineer - Computer Vision & Data Systems

Apple Seattle, WA

Seattle, WA

Today

$175k - $309k/yr Full time Artificial Intelligence Big Data Bigdata

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Job Description

Apple's Seattle team is seeking a Machine Learning Engineer with deep expertise in computer vision and large-scale data processing. The role centers on designing production-grade algorithms, building scalable data pipelines across diverse data sources, and delivering real-time sensing and data intelligence that power core Apple product experiences. Collaboration with engineering, research, and data teams will be essential, and the role also involves exploring advances in AI workflows and data operations.

Location

Seattle, WA (onsite)

Salary

USD 175,000 - 308,500 per year

Responsibilities

Architect and maintain large-scale data processing pipelines to ensure efficiency, scalability, and reliability across diverse data sources and modalities.
Develop and optimize computer vision models powering core product experiences, covering image understanding, multi-view geometry, 3D reconstruction, and visual recognition tasks.
Collaborate with engineering, research, and data teams to translate product requirements into practical technical solutions, prototype models, run large-scale experiments, enhance data quality, and ensure seamless production integration of algorithms.
Investigate advances in LLM-based agents, retrieval-augmented systems, and tool-oriented reasoning to optimize internal workflows and data operations.

Requirements

PhD in a relevant field with research focused on computer vision, large-scale data systems, or multimodal learning.
Experience designing or evaluating agentic systems, including LLM-powered tools, retrieval-augmented generation pipelines, or automated data reasoning workflows.
Familiarity with prompt engineering, tool-use patterns, and understanding of large language model behavior.
Experience deploying ML models at scale, with monitoring, evaluation, and ongoing improvement.
Knowledge of data quality assessment, dataset curation methodologies, and evaluation frameworks.
Experience optimizing models for GPUs, large-batch training, or distributed training.
Strong cross-functional collaboration skills and the ability to lead technical initiatives.
Solid foundation in computer vision with experience in deep learning-based vision models and areas such as detection, segmentation, 3D vision, geometric methods, tracking, or self-supervised learning.
Hands-on development of machine learning models using PyTorch or TensorFlow.
Experience building or optimizing large-scale data pipelines, including distributed ETL, dataset generation, annotation workflows, data validation, or high-throughput processing.
Proficiency in Python or C++ for algorithm development and data processing.
Experience with distributed computing frameworks such as Spark or Ray.

Technologies

PyTorch, TensorFlow, Python, C++, Spark, Ray

Benefits

Base pay range: $175,000 - $308,500 per year.
Opportunity to participate in discretionary employee stock programs enabling share ownership.
Eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount through the Employee Stock Purchase Plan.
Comprehensive medical and dental coverage, retirement benefits, discounts on products and free services, and tuition reimbursement for education related to advancing your career at Apple.
Possibility of discretionary bonuses or commission payments and relocation assistance.
Note: Apple benefits, compensation, and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.