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Today

Senior Data Engineer (Foundations)

Stellantis Auburn Hills, MI

Auburn Hills, MI

Today

Full time Senior Apache Airflow Aws Data Engineer

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Job Description

Senior Data Engineer role focused on building and evolving the shared ingestion platform for company-wide data delivery.

Responsibilities

Design and implement reusable ingestion components using dlt and dbt-core for both structured and unstructured sources
Build ingestion pipelines that support high-volume, append-heavy, and schema-drifting data patterns
Own the Apache Airflow platform end-to-end: extend and maintain DAGs and shared operators
Handle deployments and version upgrades for Airflow and provide hands-on support to consuming teams
Deliver incremental loading strategies with data quality checks and production-ready lineage metadata across pipelines
Identify and remove redundant ingestion patterns across teams, driving standardization onto Platform Foundation components
Partner with Solution Architects to evolve platform architecture for new data sources and changing business requirements
Support data product exposure by defining and implementing governed interfaces for reliable internal access
Contribute to infrastructure managed with Terraform; participate in multi-cloud deployment patterns (AWS and Azure)
Use and evaluate AI-assisted development tools (e.g., GitHub Copilot, Claude Code) to accelerate platform Foundation delivery
Promote AI tooling adoption within the squad, including best practices and guardrails for AI-generated code review
Explore AI-powered options for internal platform documentation and self-service enablement (e.g., RAG pipelines, LLM-assisted data cataloguing)
Maintain and improve CI/CD pipelines using TeamCity and GitHub Actions for platform Foundation components
Define and enforce observability standards, including DAG/Task-level alerting and SLA tracking
Participate in on-call rotation for critical ingestion pipelines and drive post-incident improvements
Create and maintain Platform Foundation documentation, runbooks, and enablement materials for consuming squads
Translate ambiguous or evolving business requirements into concrete technical designs, including challenging scope when needed
Mentor mid-level engineers and participate in hiring and technical assessments

Requirements

Bachelor’s degree in Business, Information Systems, Data/Analytics, Computer Science, or a related field
Minimum 5 years in data engineering, including at least 2 years in a senior or platform-level position
Proven experience building production ingestion and transformation pipelines at scale
Experience contributing to shared platform or internal developer tooling used by multiple teams
Python: idiomatic, testable, production-grade code (not just scripting)
dbt-core: advanced modeling (custom materializations), testing, documentation, packages
Apache Airflow: DAG design patterns, custom operators, dynamic task mapping, SLA management
Comfort with one or more major cloud data platforms (e.g., Snowflake, BigQuery, Databricks, Microsoft Fabric)
SQL: complex analytical queries, window functions, query profiling
Git and CI/CD: trunk-based development, automated testing gates, pipeline-as-code
Daily user of AI coding assistants (Copilot, Claude Code, or equivalent)
Understands the limits of AI-generated code and performs rigorous review rather than blind trust
Interest in LLM-powered data tooling (e.g., RAG pipelines, Cortex, semantic layers) is a plus

Tech Stack

dlt
dbt-core
Apache Airflow
Terraform
AWS, Azure
Python
Git
TeamCity, GitHub Actions
Snowflake, BigQuery, Databricks, Microsoft Fabric
SQL
GitHub Copilot, Claude Code
RAG pipelines, LLM-assisted data cataloguing
Cortex, semantic layers

AI & Modern Tooling

Daily use of AI coding assistants (Copilot, Claude Code or equivalent)
Knows AI-generated code limitations and applies rigorous review
Interest in LLM-powered data tooling is a plus (RAG pipelines, Cortex, semantic layers)

Location

Auburn Hills, MI (onsite)

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