Delta Live Tables

Delta Live Tables Developer Jobs

3 jobs found

16d ago

Sr Databricks Data Engineer

Deloitte Sacramento, CA

Sacramento, CA

16d ago

$138k - $194k/yr Full time Autoloader Big Data Bigdata

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Job Description

This onsite role, positioned as a Senior Consultant - Databricks Engineer with Deloitte, centers on designing, building, and optimizing cloud-based data engineering solutions to modernize data platforms and enable analytics and AI at enterprise scale.

Responsibilities

Promote and formalize best practices for data architecture, integration, and modeling across the organization.
Own the design, development, and ongoing maintenance of scalable data pipelines and architectures to support large-scale enterprise data needs.
Drive improvements in data quality, operational efficiency, and the scalability of data processes.
Lead and mentor teams of data engineers and architects; assess, pilot, and integrate new big data and analytics technologies to keep the organization at the cutting edge.
Advise on data governance, security, and compliance strategies tailored to modern cloud data ecosystems.
Translate technical concepts into business value for executives, business leads, and technology stakeholders.
Oversee DevOps and automation practices to enable CI/CD pipelines with tools such as Azure DevOps, AWS CodePipeline, Jenkins, TFS, and PowerShell.
Provide clear technical guidance to colleagues and project teams.

Requirements

Ability to work independently and collaboratively as part of a team.
Effective written and verbal communication skills.
Meticulous attention to detail and a commitment to high-quality work product.
Ability to build and sustain professional relationships across stakeholders.
Experience to lead projects or workstreams with accountability for outcomes.
Capacity to manage and prioritize multiple tasks in a fast-paced, dynamic environment.
Strong interpersonal skills and a professional demeanor.
Proven ability to meet deadlines.

Technologies

Databricks, AWS, Azure, and Google Cloud Platform (GCP)
Delta Lake, Apache Spark, PySpark
Unity Catalog, Delta Live Tables, Autoloader
Structured Streaming, Databricks Workflows
Apache Airflow
Azure DevOps, AWS CodePipeline, Jenkins, TFS, PowerShell
Databricks Lakehouse concepts and related tooling

Education and Experience

Qualifications Required
Bachelor's degree in Computer Science, Engineering, or a related field
5+ years of hands-on data engineering experience with a focus on Databricks on AWS, Azure, or GCP
Experience with Lakehouse architecture, Apache Spark, Delta Lake, cloud-native databases, storage solutions, and distributed compute platforms
Experience with data warehousing, 3NF, dimensional modeling, enterprise data lakes, incremental data loads, and metadata-driven ingestion and data quality frameworks using PySpark
1+ year leading complex, cross-functional data projects and technical teams, including Delta Live Tables, Autoloader, Structured Streaming, Databricks Workflows, Apache Airflow, Unity Catalog, CI/CD pipelines, and performance optimization
Ability to travel 50 percent on average based on client engagement
Limited immigration sponsorship may be available

Preferred Qualifications

Master’s degree in Computer Science, Engineering, or a related field
Experience across one or more cloud ecosystems (AWS, Azure, GCP) and associated big data services
Experience tuning and optimizing performance in Databricks and Apache Spark environments
Experience with Databricks Lakeflow
Experience with artificial intelligence and machine learning solutions

Location

Location: Sacramento, CA (onsite)

Compensation

Salary: USD 137,500 - 193,600 per year

Travel and Work Scope

Travel: Up to 50% on average, depending on client engagements and project requirements.

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22d ago

Sr Databricks Data Engineer

Deloitte Seattle, WA

Seattle, WA

22d ago

$138k - $194k/yr Full time Apache Airflow Automation Azure

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Job Description

Sr Databricks Data Engineer role with Deloitte in Seattle, WA (onsite), offering USD 137,500 - 193,600 per yearly and travel up to 50%.

Responsibilities

Define and codify best practice standards for data architecture, integration, and data modeling, and promote their adoption across projects.
Take ownership of designing, building, and sustaining robust data pipelines and architectures that serve enterprise-scale data needs.
Lead initiatives to boost data quality, streamline operations, and scale data processing processes.
Assess, pilot, and adopt emerging big data and analytics technologies to keep the organization at the forefront.
Mentor and develop data engineering and architecture teams to support technical growth and successful project delivery.
Advise on, design, and implement governance, security, and compliance frameworks for modern cloud data ecosystems.
Translate complex technical concepts and business value to executives, business leaders, and technology stakeholders.
Oversee CI/CD adoption and automation using tools like Azure DevOps, AWS Code Pipeline, Jenkins, TFS, and PowerShell to streamline deployments and operations.
Provide clear guidance to team members and stakeholders.

Requirements

Bachelor's degree in Computer Science, Engineering, or a related field
5+ years of hands-on data engineering experience with Databricks on AWS, Azure, or GCP
Experience with Lakehouse architectures, Apache Spark, Delta Lake, cloud-native databases and storage solutions, and distributed compute platforms
Experience with data warehousing, 3NF, dimensional modeling, enterprise data lakes, incremental data loads, and metadata-driven ingestion and data quality frameworks using PySpark
1+ year leading complex, cross-functional data projects and technical teams, including Delta Live Tables, Autoloader, Structured Streaming, Databricks Workflows, Apache Airflow, Unity Catalog, automated CI/CD pipelines, and optimization of data pipelines, code, and compute resources
Ability to travel 50% on average based on client work
Limited immigration sponsorship may be available
Master's degree in Computer Science, Engineering, or a related field
Experience in one or more of AWS, Azure, and GCP cloud ecosystems and their big data services
Experience tuning and optimizing performance in Databricks and Apache Spark environments
Experience with Databricks Lakeflow
Experience with artificial intelligence and machine learning solutions

Technologies

Databricks
Delta Lake
Delta Live Tables
Autoloader
Structured Streaming
Databricks Workflows
Unity Catalog
Apache Airflow
Azure DevOps
AWS Code Pipeline
Jenkins
TFS
PowerShell
PySpark
Apache Spark
Databricks Lakeflow
AWS
Azure
GCP

Benefits

Discretionary annual incentive program
Core Talent Model benefits package
Reasonable accommodations for people with disabilities

The Team

Deloitte's Core AI and Data practice assists clients in modernizing data platforms, strengthening enterprise data foundations, and scaling analytics and AI capabilities across the organization. The team designs, engineers, and deploys cloud-based data solutions that support informed decision making, drive innovation, and enable large-scale transformation. Practitioners collaborate across business and technology functions to tackle data modernization challenges.

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25d ago

Sr Databricks Data Engineer

Deloitte Nashville, TN

Nashville, TN

25d ago

$138k - $194k/yr Full time Analytics Azure Azure Data Lake Storage

Apply Now

Job Description

Join Deloitte's AI and Data practice in Nashville, onsite, as a Senior Databricks Data Engineer. This role focuses on designing, building, and optimizing cloud-based data engineering solutions on Databricks to modernize data platforms and enable analytics and AI use cases. Compensation ranges from USD 137,500 to 193,600 per year.

Benefits

Discretionary annual incentive program

Responsibilities

Define and promote best-in-class data architecture, integration, and modelling practices, with clear documentation of standards.
Own the design, development, and maintenance of robust data pipelines and architectures that support enterprise-scale data needs.
Lead initiatives to improve data quality, operational efficiency, and process scalability.
Assess, pilot, and integrate new big data and analytics technologies, while guiding and mentoring teams of data engineers and architects to ensure successful project delivery.
Advise on governance, security, and compliance strategies tailored to modern cloud data ecosystems and implement them as needed.
Translate technical concepts and business value for executives, business leads, and technology teams.
Oversee CI/CD practices with tools such as Azure DevOps, AWS Code Pipeline, Jenkins, TFS, or PowerShell to streamline deployments and operations.
Provide clear guidance to others to support project success.

Requirements

Ability to work independently and as part of a team.
Effective written and verbal communication.
Meticulous attention to detail and a commitment to quality.
Ability to build and sustain professional relationships.
Experience leading projects or workstreams.
Ability to manage and prioritize multiple tasks in a fast-paced environment.
Strong interpersonal skills and professional demeanor.
Ability to meet deadlines.
Bachelor's degree in Computer Science, Engineering, or a related field.
5+ years of hands-on data engineering experience focusing on Databricks across AWS, Azure, or GCP.
Experience with Lakehouse architecture, Apache Spark, Delta Lake, cloud-native databases, storage solutions, and distributed compute platforms.
Experience with data warehousing, 3NF, dimensional modeling, enterprise data lakes, incremental data loads, and metadata-driven ingestion and data quality frameworks using PySpark.
1+ year leading complex, cross-functional data projects and technical teams, including Delta Live Tables, Autoloader, Structured Streaming, Databricks Workflows, Apache Airflow, Unity Catalog, automated CI/CD pipelines, and performance optimization of data pipelines, code, and compute resources.
Ability to travel 50 percent on average.
Limited immigration sponsorship may be available.
Master's degree in Computer Science, Engineering, or a related field.
Experience in one or more cloud ecosystems (AWS, Azure, or GCP) and associated big data services.
Experience tuning and optimizing performance in Databricks and Apache Spark environments.
Experience with Databricks Lakeflow.
Experience with artificial intelligence and machine learning solutions.

Technologies

Azure DevOps
AWS Code Pipeline
Jenkins
TFS
PowerShell
Databricks
AWS
Microsoft Azure
Google Cloud Platform (GCP)
Lakehouse architecture
Apache Spark
Delta Lake
cloud-native databases
storage solutions
distributed compute platforms
PySpark
Delta Live Tables
Autoloader
Structured Streaming
Databricks Workflows
Apache Airflow
Unity Catalog
CI/CD pipelines
Databricks Lakeflow

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