• Design, build, and operate scalable, production-grade data pipelines and curated datasets powering ads optimization and ML systems. • Own end-to-end offline data flows from raw event ingestion to feature-ready datasets ensuring correctness, reproducibility, and SLA compliance. • Develop and maintain large-scale batch and streaming workflows (Python / Java / SQL) with strong focus on performance, cost-efficiency, and reliability. • Contribute to our Feature Store platform, including collaboration with the high-throughput online serving layer (Go-based services). • Translate complex product and monetization logic into durable, extensible data models serving analytics and machine learning use cases. • Improve observability, validation frameworks, and data quality standards across pipelines. • Drive architectural decisions and engineering best practices within the Feature Platform team.

• Contribute to the design, orchestration, and development of ongoing data science projects from data ingestion to presentation • Work with platform engineers and others to develop tools/frameworks needed to carry out projects • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. • Synthesize insights from raw data • Build dashboards and other visualizations; communicate findings internally and externally • Research new data engineering and analytics methodologies with minimal guidance and support from other team members • Build ad hoc pipelines and infrastructure in the cloud to unblock analytical projects as needed • Write, test, and deploy efficient, scalable code to production that impacts millions of individuals • Generate ideas for new initiatives and technologies • Communicate with project leads, product managers and other software developers

• Review customer data (CSVs, spreadsheets, software databases) to assess structure, quality, and completeness • Map legacy data fields to our platform’s schema using internal tools, AI tools (such as ChatGPT), or custom scripts • Transform, clean, and normalize customer data for migration into the platform • Execute and validate data imports in customer environments to ensure accuracy and completeness • Identify and troubleshoot errors throughout the migration process • Manually enter data where automation is not feasible • Become a product expert capable of setting up configurations on behalf of customers • Coordinate with onboarding specialists and customers to collect requirements and resolve data issues • Communicate migration status, clarify data concerns, and ensure customers understand field-level discrepancies • Collaborate with product and engineering teams to report bugs and suggest tooling improvements • Document migration processes and maintain internal guides to ensure consistency and scalability

• Engage in planning, analysis, design, and development of data management, data integration, data warehouse, and business intelligence solutions. • Engage in discussions with the team, clients, and project sponsors to determine project goals and set priorities. • Convert business and technical requirements into detailed data analysis and system design specifications. • Utilize database, programming, and ETL tools to implement and maintain data management and warehousing solutions, creating valuable data analytics assets for clients. • Work closely with clients and the BerryDunn team to analyze systems, gather requirements, map data pipelines, and assess data quality. • Conduct data quality analysis, investigate and resolve issues to ensure data integrity and accuracy. • Create and deliver reports and analytic applications using suitable business intelligence or custom tools to meet client needs. • Improve efficiency and reliability of client and BerryDunn data processes through innovative solutions and best practices. • Use Artificial Intelligence tools to enhance productivity and improve project deliverables. • Collaborate with other groups within BerryDunn to provide support for data and system analysis, data pipeline engineering, and data architecture. • Provide guidance and mentorship to junior team members, fostering a culture of continuous learning and improvement. • Keep abreast of the latest trends and technologies in data engineering, healthcare analytics, and data science to ensure BerryDunn remains at the forefront of the industry. • Ensure all data solutions comply with industry standards, regulations, and security protocols, particularly those specific to healthcare.