Staff Data Engineer - Ireland

Job description

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at jnj.com. As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit. Job Function: Data Analytics & Computational Sciences Job Sub Function: Data Engineering Job Category: Scientific/Technology All Job Posting Locations: Ringaskiddy, Cork, Ireland Job Description: Orthopedics Supply Chain is recruiting for a Staff Data Engineer located in Raynham, MA; Raritan, NJ;Palm Beach Gardens, FL; Warsaw IN; Cork, IE; At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at https://www.jnj.com/ Please note that this role is available across multiple countries and may be posted under different requisition numbers to meet local requirements. While you are welcome to apply to any or all of the postings, we recommend focusing on the country(s) that align with your preferred location(s): USA – Req. # R-096100 Whether you apply to one or several, your applications will be considered as a single submission. Johnson & Johnson announced plans to separate its Orthopedics business into a standalone company, operating as DePuy Synthes. The planned separation is anticipated to be completed within 18 to 24 months, subject to legal requirements (including consultation with works councils and other employee representative bodies, as may be required), regulatory approvals, and other customary conditions and approvals. Should you accept this position, it is anticipated that, following the transaction, you would join DePuy Synthes, and your employment would be governed by its employment processes, programs, policies, and benefit plans. Details of any planned changes would be shared at an appropriate time and subject to any necessary consultation processes. What's in it for you? 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. Key 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 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. Proven skill in converting business needs into architecture, user stories, and executable delivery plans. Demonstrated ability to coordinate distributed engineering teams, contractors, and vendors. Excellent communication, facilitation, and relationship-building skills across technical, product, and business audiences. Knowledge of Power BI, Tableau, or enterprise BI platforms. Knowledge of workflow automation tools (e.g., Power Automate, Blue Prism, UiPath, or Amazon Quick Flows). Preferred: Experience supporting Agile product teams and mentoring engineers in fast-paced environments. Familiarity with end-to-end supply chain domains (planning, manufacturing, procurement, distribution, logistics) within MedTech or a similar regulated industry. Knowledge of enterprise systems of record such as SAP, ERP, MES, PLM, and CRM, including legacy or fragmented data environments. Experience with Unity Catalog, data governance, lineage, metadata management, and observability frameworks. Hands-on experience with modern Databricks capabilities (Lakeflow, Spark Declarative Pipelines, Mosaic AI, AI/BI Genie) and AI-assisted development tools such as GitHub Copilot, Claude Code, Amazon Q Developer, or Cursor. Experience with dbt, Airflow, Terraform, Databricks Asset Bundles, GitHub Actions, or