Data Engineer

AstraZeneca is a pharmaceutical manufacturing company focused on addressing unmet patient needs worldwide. Its Medical Data Team generates and communicates medical evidence, while the medical data foundation makes AI-ready data available to the Medical business.

• Establish a repeatable process for onboarding new data sets into the medical data foundation, ensuring high quality, alignment with business rules, findability, and accessibility;
• Develop data strategies with internal stakeholders to gain deeper insight into the business, patients’ journeys, and customer engagement;
• Define the common data model vision, data sourcing, transformation, and reconciliation approaches;
• Identify data sources and drive data-related key design decisions;
• Monitor data quality, global data integrity, and reporting consistency, and communicate issues to the appropriate teams;
• Oversee data accuracy processes, goals, and assessments, and communicate data models to development team members;
• Query data sets to validate business rules and requirements and resolve conflicts across and within systems;
• Support the overall data architecture, prioritize and recommend initiatives, and deploy solutions to improve it;
• Collaborate with IT on data lifecycle activities, including modeling for Data Hub, Data Warehouse, Data Marts, and Analytic Platform projects;
• Ensure consistency of data processes and usage and champion data management best practices;
• Cooperate with vendors and stakeholders across functions and seniority levels;
• Promote data management best practices and work with IT and Privacy teams to maintain governance, protection, and security standards;
• Understand new data privacy and management guidelines and drive required implementation actions;
• Scan the marketplace for best-in-class data capabilities that can be adapted and leveraged;
• Support Medical platforms in maintaining data integrity and accuracy across ingestion, transformation, and reporting workflows.

• University degree; a Master’s degree is preferred;
• At least 5 years of experience in business analysis, financial analysis, or a related field;
• At least 3 years of experience in medical data analytics;
• At least 2 years of data modeling experience;
• Experience working and delivering in a global organization;
• Experience working on cross-functional teams in a matrix organization;
• Experience in the pharmaceutical or healthcare industry;
• Expert knowledge of logical and physical modeling, mappings, conformed dimensions, SCDs, and enterprise data platforms such as Snowflake or Synapse;
• At least 3 years of experience building ELT/ETL pipelines with tools such as ADF, Databricks, or dbt, including lineage and orchestration;
• Experience setting up data quality rules, monitoring, issue resolution, taxonomies, controlled vocabularies, and metadata with tools such as Collibra, Alation, or Informatica;
• Advanced SQL skills, including joins and window functions, for validating business rules and reconciling cross-system conflicts;
• Working knowledge of data protection and security and experience partnering with IT and Privacy teams to implement controls;
• Ability to influence Medical, IT, and vendor stakeholders, present complex topics clearly, and facilitate alignment on standards and definitions;
• Ability to plan, prioritize, and deliver multi-workstream programs, manage resources and outcomes, and solve problems in ambiguous environments;
• Excellent communication and presentation skills in English;
• Nice to have: Python and SQL for data engineering and validation, defining OKRs and metrics, tracking value realization, building or deploying models for medical text, knowledge of analytics, ML, AI-ready datasets, taxonomies, ontologies, knowledge graphs, and semantic structures.

• Hybrid work requires 3 days per week from the office in Warsaw;
• Multisport card;
• Pension plan;
• Life insurance;
• After-work events;
• Private medical care;
• Lunch card;
• Collaborative, bright, and spacious office environment.