Staff Data Engineer

fanaticsfbg; United States; Remote; USD 181,000 - 238,000; Full time

Benefits offered by this job

Some interview/onboarding in person

Job summary

fanaticsfbg is seeking a Senior Data Engineer to set the technical direction for a data platform that ingests data from source systems into reliable, decision-ready data. You will own architecture across ingestion, orchestration, governance, and delivery, solving complex problems beyond runbooks.

You will lead the creation of reusable standards, drive reliability improvements, and mentor engineers while partnering with analytics, product, and business teams.

Qualifications

• Eight+ years in software or data engineering with production data platforms at scale.
• Experience delivering large cross-team data systems from unclear requirements through production operation.
• Advanced Python and SQL skills with deep ETL/ELT experience.
• Deep experience with Airflow or Managed Workflows for Apache Airflow.
• Strong knowledge of reliability concepts like idempotency, backfills, schema evolution, late-arriving data, and quality checks.
• Hands-on with Snowflake, Databricks, AWS, dbt, Tableau, MongoDB, and PostgreSQL.
• Experience building governance capabilities and reusable frameworks, plus CI/CD and code review practices.
• Ability to mentor, build alignment across teams, and communicate decisions via designs and incident reports.

Responsibilities

• Architect ingestion pipelines, orchestration, and data delivery systems; write design guidance for others to implement.
• Establish reusable standards for pipelines, Airflow workflows, testing, monitoring, and data catalog registration.
• Investigate and fix integrity, performance, and reliability issues; automate recurring failures into runbooks.
• Define reliability goals and alerting practices; improve on-call health and reduce operational toil.
• Set data security and governance practices, including access controls, masking, classification, and lineage.
• Design integrations for reverse ETL and downstream delivery, defining service expectations and failure handling.
• Guide platform choices and cost planning across data and cloud services; review high-risk changes.
• Collaborate with analytics, product, data science, and business partners; mentor engineers and shape technical direction.

Skills

Python

SQL

Airflow

ETL/ELT

Data governance

Cloud/WLat

CI/CD

Mentoring

Reliability

Tools

Snowflake

Databricks

AWS

dbt

Tableau

MongoDB

PostgreSQL

Job description

Role overview

Set technical direction for a data engineering platform that moves information from source systems into reliable, decision-ready data. This senior individual-contributor role owns architecture and standards across ingestion, orchestration, governance, and delivery, and takes on complex problems that require judgment beyond established runbooks.

Responsibilities

• Architect ingestion pipelines, orchestration, and data delivery systems; write design guidance that other engineers can implement.
• Establish reusable standards for pipelines, Airflow workflows, testing, monitoring, and data catalog registration.
• Lead investigation of difficult integrity, performance, and reliability issues, turning recurring failures into systemic fixes, automation, or runbooks.
• Define reliability goals and alerting practices, improve on-call health, and reduce operational toil.
• Set data security and governance practices, including access controls, sensitive-data masking, classification, and lineage.
• Design integrations for reverse ETL and downstream delivery, specifying service expectations and failure handling.
• Guide platform choices and cost planning across data and cloud services; review designs and high-risk changes for failure modes and downstream impact.
• Work with analytics, product, data science, and business partners; mentor engineers and help shape technical direction.

Requirements

• At least eight years of software or data engineering experience, including ownership of production data platforms at scale.
• Track record delivering large, cross-team data systems from unclear requirements through production operation.
• Advanced Python and SQL skills, with deep ETL/ELT experience for complex, high-volume transformations.
• Deep experience with Airflow or Managed Workflows for Apache Airflow, including large-scale workflow design and operations.
• Strong command of pipeline reliability concepts such as idempotency, backfills, schema evolution, late-arriving data, quality checks, and recovery.
• Hands-on experience with several of Snowflake, Databricks, AWS, dbt, Tableau, MongoDB, and PostgreSQL.
• Experience building governance capabilities and reusable frameworks, plus strong testing, CI/CD, and code review practices.
• Ability to mentor, build alignment across teams, and communicate decisions through design documents, trade-off analysis, and incident reports.

Nice to have

• Experience with reverse ETL, streaming systems such as Kafka, observability tools, cloud cost governance, or major platform migrations.
• Background in gaming, betting, e-commerce, or another regulated sector.

Benefits and work setup

• Some interview and onboarding activities may be in person, depending on the role and location.

The listed US base salary range is $180,500–$237,500, subject to geographic compensation zones.