Staff Data Engineer – Lakehouse & AI Data Architect

Antler Co; Mooresville (IN); On-site; USD 150,000 - 190,000; Full time

Job summary

Johnson & Johnson is seeking a Staff Data Engineer to lead the modern data foundation for Orthopaedics Supply Chain. You will architect lakehouse platforms on Databricks and AWS, delivering governed, reusable data products for analytics, reporting, AI and operations.

You will collaborate with Product Owners, business teams, data engineers, ML groups, and external partners to turn business problems into scalable technical solutions.

Qualifications

• Experience with modern lakehouse architectures on cloud platforms.
• Ability to design complex data pipelines for analytics and ML.
• Familiarity with governance, security, and cost controls.

Responsibilities

• Provide technical leadership for the Data Foundation initiative to modernize the data ecosystem.
• Design pipelines and architectures using Databricks, AWS, Python, SQL, Spark, and Delta Lake.
• Translate business needs into architecture decisions and reusable patterns.
• Blueprint batch, streaming, and event-driven pipelines for analytics and AI/ML.
• Collaborate with Product Owners, Supply Chain, governance, AI/ML teams, IT partners.
• Lead architecture discussions ensuring scalability, reliability, and cost efficiency.
• Break initiatives into work packages, user stories, and acceptance criteria.
• Coordinate contractor and vendor delivery and direction.
• Set standards for data modeling, CI/CD, observability, and data quality.
• Lead hands-on reviews with Databricks, PySpark, Spark SQL, Python, SQL, dbt, Airflow.
• Promote AI-assisted engineering to improve quality and velocity.
• Mentor engineers through design and code reviews.

Tools

Databricks

AWS

Python

SQL

Spark

Delta Lake

PySpark

dbt

Airflow

Job description

Johnson & Johnson is seeking a Staff Data Engineer to lead the modern data foundation for Orthopaedics Supply Chain. You will architect lakehouse platforms on Databricks and AWS, delivering governed, reusable data products for analytics, reporting, AI and operations.

You will collaborate with Product Owners, business teams, data engineers, ML groups, and external partners to turn business problems into scalable technical solutions.