Staff Data Engineer

About the role

Orthopedics Supply Chain is recruiting for a Staff Data Engineer located in Raynham, MA; Raritan, NJ; Palm Beach Gardens, FL; Mooresville, IN; Warsaw, IN; Cork, IE. In this role, you will play a pivotal technical leadership role in building the modern data foundation that powers digital products across the Orthopaedics Supply Chain. You will help design lakehouse architecture on Databricks and AWS while enabling governed, reusable, business-ready data products for analytics, reporting, AI, and operational decision-making. The role suits an expert professional who can lead across solution architecture, pipeline design, engineering standards, and cross-team delivery. You will work closely with Product Owners, business teams, data engineers, machine learning teams, and external delivery partners to turn business problems into practical technical solutions and executable plans. You will also help advance modern engineering practices, including AI-assisted development, reusable patterns, data quality automation, and observability. This is an opportunity to make a meaningful impact if hands-on architecture and solving complex data challenges at scale are what energize you. This position may require up to 10% domestic and international travel.

Responsibilities

• Provide technical leadership for the Data Foundation initiative to modernize the enterprise data ecosystem through lakehouse architecture and cloud platform capabilities.
• Design complex data pipelines, integration patterns, and architecture using Databricks, AWS, Python, SQL, Spark, and Delta Lake.
• Turn business requirements and technical challenges into architecture decisions, implementation plans, and reusable patterns.
• Develop blueprints for batch, streaming, and event-driven pipelines that support analytics, BI, AI/ML, and digital product use cases.
• Partner with Product Owners, Supply Chain teams, data governance, AI and ML groups, and IT partners to align delivery with measurable business outcomes.
• Lead architecture and design discussions, ensuring solutions meet standards for scalability, reliability, quality, security, maintainability, and cost efficiency.
• Break down large initiatives into work packages, user stories, and acceptance criteria for internal engineers and external contractors.
• Coordinate contractor and vendor execution by assigning work, reviewing deliverables, and providing technical direction.
• Set clear standards for data modeling, modularity, reuse, automated testing, CI/CD, data quality, observability, lineage, and operational support.
• Lead hands-on development and technical reviews with Databricks, PySpark, Spark SQL, Python, SQL, dbt, and orchestration tools like Airflow.
• Champion responsible adoption of AI-assisted engineering to improve quality, documentation, testing, and delivery velocity.
• Mentor engineers and contractors through design and code reviews and architecture guidance (no direct people-management responsibility).
• Contribute to technical governance forums, architecture standards, and operating-model practices that improve consistency and reuse.

Qualifications

• Education: A minimum of a Bachelor’s degree and/or equivalent University degree is required; a focused degree in Computer Science, Engineering, Applied Mathematics, Information Systems, or a related field preferred.
• Required Minimum four (4) years of relevant professional work experience.
• Experience in data engineering, data architecture, or platform engineering (consistent with J&J leveling).
• Strong hands-on experience across Databricks, Apache Spark, PySpark, Spark SQL, Python, SQL, and Delta Lake.
• Strong experience with AWS cloud data services; Azure experience desirable.
• Proven expertise in modern data and lakehouse architecture, enterprise data platforms, dimensional modeling, and pipeline design.
• Experience designing batch, real-time, and event-based processing for enterprise-scale workloads.
• Experience with CI/CD, Git-based development, automated testing, deployment patterns, and production support.