Lead Data Engineer

Work Flexibility: Hybrid

Lead Data Engineer
This role is responsible for designing, building, and maintaining the infrastructure that collects, stores, and processes raw data, transforming it into usable information for analysis by business analysts for the Joint Replacement franchise. This role is responsible for building data pipelines, managing data warehouses/lakes, ensuring data cleanliness/quality, and collaborating with stakeholders to understand data requirements.

What you will do:

• Data management and integration:  design, build, and maintain data pipelines to extract, transform, and load data from various internal sources (multiple ERP systems and business systems) in various master data structures into an integrated data lake, accessible by Stryker-standard business analysis tools. 
• Data quality assurance:  ensure data timeliness, integrity and cleanliness/quality by monitoring the existing and incoming data, and reporting exceptions.  Investigate and remedy exceptions. Collaborate with data and system owners to define, implement, and maintain systematic validation processes and business rules for ongoing data quality checks.
• Infrastructure management:  monitor system performance, troubleshoot issues, and implement optimizations to improve data processing speed and scalability.
• Data security:  implement data security measures to protect sensitive information and maintain access approval process.
• Collaboration with stakeholders:  work closely with business analysts and divisional planning teams to understand data needs and deliver tailored solutions
• Process development: create processes for effective data ingestion, quality, maintenance and automation manual processes.  Establish best practices and global standards for data management. Lead development/maintenance of technical documentation for key systems and data assets.
• Documentation: document data sources, flow, systems, tools, and process steps
• IT integration:  coordinate with IT to ensure that the necessary infrastructure is rolled out and maintained, and that current technology supports the divisions’ goals and co-build and self-service analytics ecosystem. Able to contribute to discussions on identifying opportunities in data architecture to enable business opportunities with key stakeholders.

What you will need:

• Bachelors Degree in Computer Science or similar technical discipline

• 5-8 years of experience in data engineering or related field

• Deep competencies in SQL, Python, data warehousing technologies, big data technologies, data quality tools, data integration tools, data lineage tools, and data analytics and business intelligence tools.  Strong analytical approach to problem solving, communication skills, and relationship management.

• Experience with Databricks, Unity Catalog, Azure Data Lake, Azure Data Factory, Power BI Suite, Rest APIs (including Power BI)

• Experience with SAP modules, Manufacturing Resource Planning Systems, Medallion Architecture, Cloud-based data ecosystem, RPA/automation tools

Travel Percentage: 10%