Cloud Dataflow

Cloud Dataflow Engineer Jobs

3 jobs found

9d ago

Data Engineer

Major League Baseball (MLB) New York, NY

New York, NY

9d ago

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

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Job Description

Join MLB's LAI team in New York on site to build production data pipelines using Airflow and dbt on Google Cloud Platform. You will design pipelines, data models, and infrastructure that power analytics across clubs and the Commissioner's Office. This role offers a collaborative culture, emphasis on data quality and governance, and the opportunity to influence league analytics with hands-on engineering work.

Responsibilities

Develop production-grade pipelines with Airflow and dbt to orchestrate batch and streaming transformations on GCP, delivering trusted data for downstream analysts and engineers.
Design clean, layered data models (staging, intermediate, mart) that serve as the league's single source of truth, applying dbt best practices for materialization, testing, and documentation.
Operate the ingestion layer with Pub/Sub, GCS, Dataflow, and Knowledge Catalog DataPlex to land both batch and streaming sources into the lakehouse.
Establish observability and monitoring standards to surface data quality issues proactively before stakeholders notice them.
Manage code through GitHub-based CI/CD, contributing to deployment workflows that keep the platform reliable and changes safe.
Adhere to data governance practices to keep proprietary baseball data secure and compliant.

Requirements

2 to 4 years of production data engineering experience.
Expert-level SQL, capable of writing complex freehand queries and reviewing others' queries to spot issues.
Strong Python skills for data processing, scripting, and automation.
Hands-on dbt experience building models across staging, intermediate, and mart layers, with tests and production deployments.
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.
Git-based development workflows, including branches, PRs, and code reviews.
Clear communication with engineers and non-engineers, receptive to feedback and collaborative in approach.
Execution mindset with the ability to 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 and MLB.TV
Discounts at MLB Store
Employee Assistance Programs (EAP)
Onsite and Online Training and Development Programs
Tuition Reimbursement
Disability Benefits (short term and long term)
Life and Accidental Death Insurance
Pet Insurance

Salary

Base salary: $115,000 – $140,000 per year, plus bonus.

NICE-TO-HAVE

A degree in Computer Science, Engineering, or a related field, or 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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10d ago

Senior Data Engineer

Advantage Technical Chicago, IL

Chicago, IL

10d ago

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

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Job Description

Advantage Technical is seeking a Senior Data Engineer to design scalable data pipelines on Google Cloud Platform, with a focus on BigQuery and SQL. The role collaborates closely with analytics and data science teams to operationalize data assets and deliver high-quality insights. This onsite Chicago position requires four days in the office each week and offers an hourly rate of $55-$64.

Responsibilities

Design, develop, and maintain high-performance data pipelines and ETL workflows
Build 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
Implement CI/CD practices 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

Technologies

Google Cloud Platform (GCP)
BigQuery
Composer
Dataflow
GCS
DataStream
SQL
Python
Airflow
Kafka
Spark
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

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15d ago

Data Engineer

Major League Baseball New York, NY

New York, NY

15d ago

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

Apply Now

Job Description

This onsite Data Engineer role on Major League Baseball’s LAI team focuses on building and operating production data pipelines within a GCP lakehouse, leveraging Airflow and dbt to empower analytics across the league. The position is based in New York, NY.

Responsibilities

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

Requirements

2–4 years of production data engineering experience.
Expert-level SQL with the ability to craft complex queries and interpret others' code to identify issues.
Strong Python skills for data processing, scripting, and automation.
Hands-on dbt experience 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.
Git-based development workflows, including branches, PRs, and code reviews as part of daily practice.
Clear communication with both engineers and non-technical stakeholders, receptive to feedback and collaborative in approach.
Execution mindset with the ability to own a project from requirements through deployment with minimal supervision.

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 and MLB.TV
Discounts at MLB Store
Employee Assistance Programs (EAP)
Onsite and 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 related field, or 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 devise creative solutions for unusual problems

Salary Range

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

Why MLB?

Major League Baseball is one of the oldest and most storied professional sports leagues in North America. The company emphasizes growth, teamwork, and professionalism across its workforce. Successful employees demonstrate initiative, problem-solving abilities, and a team-first mindset. MLB supports its workforce by engineering experiences that position employees for success and enable high performance.

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