Stellantis

Senior Data Engineer - Platform Foundation

Stellantis • $100K — $130K *
Auburn Hills, MI 48326In-Person
Information Technology
5 - 7 years of experience
5 days ago
Job Overview by Ladders

Qualifications

  • Bachelor's in Business, IT, Data Science, Computer Science, or related field.
  • Minimum 5 years in data engineering, 2 years in a senior/platform-level role.
  • Experience in building production-grade ingestion and transformation pipelines at scale.
  • Proven contribution to shared platforms or internal developer tools used by multiple teams.
  • Strong understanding of Python, dbt-core, Apache Airflow, SQL, and cloud data platforms.

Responsibilities

  • Design and implement reusable ingestion components for structured and unstructured data.
  • Own the end-to-end Airflow platform, maintaining DAGs and extending shared operators.
  • Ensure data quality and lineage metadata for every pipeline produced.
  • Drive architectural simplification by eliminating redundant patterns across teams.
  • Collaborate with architects to evolve the platform based on new data sources.
  • Define and implement governed interfaces for reliable internal data access.
  • Mentor engineers and contribute to hiring and technical assessments.

Benefits

  • Work in a team-focused environment that encourages collaboration.
  • Professional development opportunities, including mentoring.
  • Access to cutting-edge AI development tools to boost productivity.
  • Flexibility in navigating ambiguity and shifting requirements appears encouraged.
  • Multi-cloud deployment experience enhances technical proficiencies.
Full Job Description
The Senior Data Engineer - Platform Foundation is a hands-on, senior-level contributor embedded in the Foundations squad. You will design, build, and evolve the shared ingestion platform that underpins data delivery across the company. The platform is the product - your job is to make it reliable, extensible, and easy for other teams to adopt.

The Foundations squad operates across three pillars: simplifying the overall data platform landscape by reducing complexity and consolidating redundant patterns; enabling structured and unstructured data ingestion at scale; and supporting the exposure of data products to consumers across the organization. You contribute to all three - making architectural decisions, writing production code, and enabling other teams through documentation and hands-on support.

Key Responsibilities:

Platform Foundation Development
  • Design and implement reusable ingestion components using dlt and dbt-core, covering both structured and unstructured data sources, handling high-volume, append-heavy, and schema-drifting patterns
  • Own the Airflow platform end-to-end: extend and maintain DAGs and shared operators, handle deployments and version upgrades, and provide hands-on support to consuming teams
  • Ensure incremental loading strategies, data quality checks, and lineage metadata are first-class outputs of every pipeline


Platform Simplification & Architecture
  • Identify and eliminate redundant ingestion patterns across consuming teams, drive standardization onto shared Platform Foundation components
  • Collaborate with Solution Architects to evolve the platform architecture in response to new data sources and shifting business requirements
  • Support data product exposure: define and implement governed interfaces that make data reliably accessible to internal consumers
  • Contribute to Terraform-managed infrastructure; participate in multi-cloud (AWS / Azure) deployment patterns


AI Tooling & Developer Productivity
  • Actively use and evaluate AI-assisted development tools (GitHub Copilot, Claude Code, etc.) to accelerate platform Foundation delivery
  • Champion AI tooling adoption within the squad; share best practices and guardrails around AI-generated code review
  • Explore AI-powered capabilities (RAG pipelines, LLM-assisted data cataloguing) for internal platform documentation and self-service enablement


DevOps & Reliability
  • Maintain and improve CI/CD pipelines (TeamCity, GitHub Actions) for platform Foundation components
  • Define and enforce observability standards: DAG/Task-level alerting, SLA tracking
  • Participate in on-call rotation for critical ingestion pipelines; drive post-incident improvements


Team Enablement & Stakeholder Management
  • Produce platform Foundation documentation, runbooks, and enablement materials for consuming squads
  • Translate ambiguous or moving business requirements into concrete technical designs - comfortable challenging scope when needed
  • Mentor mid-level engineers; participate in hiring and technical assessments


Basic Qualifications:
  • Bachelor's degree in Business, Information Systems, Data/Analytics, Computer Science, or related field
  • Minimum 5 years in data engineering roles, with at least 2 years in a senior / platform-level position
  • Proven track record building production ingestion and transformation pipelines at scale
  • Experience contributing to a shared platform or internal developer tooling consumed by multiple teams


Core Technical Skills:
  • Python: idiomatic, testable, production-grade code - not just scripting
  • dbt-core: advanced modelling (custom materializations), testing, documentation, packages
  • Apache Airflow: DAG design patterns, custom operators, dynamic task mapping, SLA management
  • Cloud data platforms: comfortable with one or more major cloud warehouses (Snowflake, BigQuery, Databricks, Microsoft Fabric)
  • SQL: complex analytical queries, window functions, query profiling
  • Git, CI/CD: trunk-based development, automated testing gates, pipeline-as-code

AI & Modern Tooling:
  • Daily user of AI coding assistants (Copilot, Claude Code or equivalent)
  • Understands the limits of AI-generated code - applies rigorous review, not blind trust
  • Interest in LLM-powered data tooling (RAG pipelines, Cortex, semantic layers) is a plus


Behavioral:
  • Navigates ambiguity: comfortable when requirements shift mid-sprint; drives clarification rather than waiting. Comfortable working with global teams
  • Platform mindset: builds for reuse, not one-off solutions
  • Direct communicator: raises blockers early, documents decisions, challenges assumptions constructively
  • Learner: actively tracks technology evolution

About Stellantis

Stellantis is a multinational automotive manufacturer formed in 2021 by the merger of Fiat Chrysler Automobiles and Groupe PSA. The company designs, produces, and sells a wide range of vehicles under various brands, including Alfa Romeo, Chrysler, Citroen, Dodge, DS Automobiles, Fiat, Jeep, Lancia, Maserati, Opel, Peugeot, Ram, and Vauxhall. Stellantis operates in over 130 countries and has 14 brands in its portfolio. The company is committed to sustainable mobility and has set ambitious targets for reducing its carbon footprint and increasing the share of electric vehicles in its sales.
Learn more about Stellantis
Size
400,000 employees
Market Cap
$44.9 billion
Industry
Manufacturing & Automotive
* Ladders Estimates

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