Cloud Dataflow

Cloud Dataflow Developer Jobs

3 jobs found

5d ago

Data Engineer

Major League Baseball (MLB) New York, NY

New York, NY

5d ago

$115k - $140k/yr Full time Python Analytics Apache Airflow

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Job Description

Join MLB's LAI team as a hands-on data engineer shaping production pipelines with Airflow and dbt on GCP to power analytics across clubs and the Commissioner's Office.

Responsibilities

Build production-grade pipelines using Airflow and dbt to orchestrate batch and streaming transformations across GCP, so downstream analysts and engineers can trust the data they query without checking the wiring.
Architect clean, layered data models (staging, intermediate, mart) that serve as the single source of truth for league analytics, applying dbt best practices for materialization, testing, and documentation.
Operate the ingestion layer using Pub/Sub, GCS, Dataflow, and Knowledge Catalog DataPlex to land both batch and streaming sources cleanly into the lakehouse.
Implement observability and monitoring standards so that data quality issues surface before stakeholders notice them.
Manage code through GitHub-based CI/CD, contributing to deployment workflows that keep our platform reliable and our changes safe.
Adhere to data governance practices that keep proprietary baseball data secure and compliant.

Requirements

2–4 years of production data engineering experience.
Expert-level SQL — comfortable writing complex freehand queries (sub-queries, nested logic, window functions) and reading someone else’s to spot issues.
Strong Python for data processing, scripting, and automation.
Hands-on dbt experience — built models across staging, intermediate, and mart layers, written tests, and shipped to production.
Production Airflow experience — DAG authoring, dependency management, debugging failed runs.
Deep familiarity with Google Cloud Platform (BigQuery, GCS, Pub/Sub) or equivalent depth in AWS/Azure with willingness to convert.
Git-based development workflows — branches, PRs, code reviews as a daily practice.
Clear communication with both engineers and non-engineers, receptive to feedback and able to give it kindly.
Execution mindset. You can own a project from requirements to deployment with minimal oversight.

Technologies

Airflow
dbt
Python
SQL
GitHub
BigQuery
GCS
Pub/Sub
Dataflow
Knowledge Catalog DataPlex
Terraform

Benefits

Competitive Benefits Package
Company Contributed 401K Plan
Paid Time Off and Holidays
Paid Parental Leave
Access to Free Tickets to Baseball Games & MLB.TV
Discounts at MLB Store | MLBShop.com
Employee Assistance Programs (EAP)
Onsite/Online Training & Development Programs
Tuition Reimbursement
Disability Benefits (short term and long term)
Life and Accidental Death Insurance
Pet Insurance

Salary

Base salary: USD 115,000 - 140,000 per year, plus bonus.

Nice to have

A degree in Computer Science, Engineering, or a related field — or non-traditional background with equivalent practical experience.
Experience with Terraform or other Infrastructure-as-Code tools.
Experience with AI-assisted development or enterprise AI tooling (Gemini Enterprise, Vertex AI).
A passion for baseball, or prior experience in sports, media, or entertainment.
Ability to build creative solutions for unusual problems.

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6d ago

Senior Data Engineer

Advantage Technical Chicago, IL

Chicago, IL

6d ago

$55 - $64/hr Full time Senior Apache Airflow Big Data

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Job Description

Advantage Technical offers a collaborative, data-driven environment where your work directly informs business decisions. The Senior Data Engineer will build scalable data pipelines on Google Cloud Platform with a focus on BigQuery and SQL, partnering with analytics and data science teams to unlock actionable insights. This role is based in Chicago and onsite four days per week, with an hourly rate of $55 to $64.

You will work with Google Cloud Platform services including BigQuery, Composer, Dataflow, GCS, and DataStream, along with SQL, Python, Airflow, Kafka, Spark, and Pub/Sub.

Benefits

Medical, dental, vision, and pet insurance
401(k) Retirement Savings Plans
Employee Assistance Program (EAP)
Commuter/Parking Accounts
People Perks
Health Savings Account (HSA)
AD&D Insurance

Responsibilities

Design, build, and maintain high-performance data pipelines and ETL workflows
Create and optimize data models, semantic layers, and cloud-based data solutions
Develop REST APIs and support data integration initiatives
Improve pipeline performance, scalability, reliability, and data quality
Establish CI/CD processes for data products and deployments
Troubleshoot complex data engineering and ingestion issues
Document data architecture, lineage, and operational processes
Collaborate with stakeholders across IT, reporting, product, and business teams
Mentor junior data engineers and support Agile development practices

Requirements

Bachelor’s degree in Computer Science, Engineering, or related technical field
6+ years of data engineering experience for Senior-level opportunities
Experience with Google Cloud Platform (GCP), including BigQuery, Composer, Dataflow, GCS, and DataStream
Advanced SQL skills and strong Python programming experience
Experience with Airflow, Kafka, Spark, Pub/Sub, or similar technologies
Strong knowledge of data warehousing, ETL pipelines, and cloud architecture
Excellent communication and problem-solving skills

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10d ago

Data Engineer

Major League Baseball New York, NY

New York, NY

10d ago

$115k - $140k/yr Full time Apache Airflow Automation Big Data

Apply Now

Job Description

Major League Baseball is seeking a hands-on Data Engineer to join the LAI team and shape production data pipelines that power league analytics. This onsite role in New York, NY centers on building and operating a GCP lakehouse with Airflow and dbt to deliver trusted data for analysts and engineers. You will own the end-to-end data workflow from ingestion to production monitoring.

Responsibilities

Develop production-grade pipelines with Airflow and dbt to orchestrate batch and streaming transformations across Google Cloud Platform, ensuring downstream analysts and engineers can rely on the data without tracing wiring issues.
Design layered data models (staging, intermediate, mart) as the single source of truth for league analytics, applying dbt best practices for materialization, testing, and documentation.
Manage ingestion through Pub/Sub, GCS, Dataflow, and Knowledge Catalog DataPlex to land batch and streaming sources into the lakehouse with clean, consistent landings.
Establish observability and monitoring standards to surface data quality issues before stakeholders notice them.
Maintain code with GitHub-based CI/CD and contribute to deployment workflows that keep the platform reliable and changes safe.
Follow data governance practices to keep proprietary baseball data secure and compliant.

Requirements

2 to 4 years of hands-on production data engineering experience.
Advanced SQL skills, able to craft complex queries (subqueries, nested logic, window functions) and review others' queries for issues.
Proficient Python for data processing, scripting, and automation.
Hands-on dbt experience building models across staging, intermediate, and mart layers, with tests and production deployment.
Production Airflow experience including DAG authoring, dependency management, and debugging failed runs.
Deep familiarity with Google Cloud Platform (BigQuery, GCS, Pub/Sub) or equivalent depth in AWS/Azure with willingness to convert.
Experience with Git-based development workflows including branching, pull requests, and code reviews as a daily practice.
Clear communicator with both engineers and non-engineers, receptive to feedback, and constructive in responses.
Execution-oriented mindset, able to own projects from requirements to deployment with minimal oversight.

Technologies

Airflow
dbt
BigQuery
GCS
Pub/Sub
Dataflow
Knowledge Catalog DataPlex
GitHub

Benefits

Competitive Benefits Package
Company Contributed 401K Plan
Paid Time Off and Holidays
Paid Parental Leave
Access to Free Tickets to Baseball Games & MLB.TV
Discounts at MLB Store | MLBShop.com
Employee Assistance Programs (EAP)
Onsite/Online Training & Development Programs
Tuition Reimbursement
Disability Benefits (short term and long term)
Life and Accidental Death Insurance
Pet Insurance

Nice-to-have

A degree in Computer Science, Engineering, or a related field — or non-traditional background with equivalent practical experience
Experience with Terraform or other Infrastructure-as-Code tools
Experience with AI-assisted development or enterprise AI tooling (Gemini Enterprise, Vertex AI)
A passion for baseball or prior experience in sports, media, or entertainment
Ability to build creative solutions for unusual problems

Salary

USD 115,000 - 140,000 per year, plus bonus.

Why MLB?

Major League Baseball is the historic centerpiece of professional sports in North America, known for a culture that emphasizes growth, teamwork, and professionalism. Employees thrive by taking initiative, solving problems, and putting the team first. MLB aims to empower its workforce to excel by offering experiences that position them for success.

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