Manager, Data Operations

Job description

When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform to connect, work at pace and challenge perceptions. That’s why we work, on average, a minimum of three days per week from the office. But that doesn’t mean we’re not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world. In this role, you will lead the delivery and daily operation of specialty pharmacy, specialty infusion, patient services, trade and distribution data that powers our US Commercial strategy and execution. You will transform partner data into reliable, governed assets for reporting, analytics, field operations and business decisions. This is a hands-on position where you will dig into SQL, understand pipelines end to end, and coordinate business, engineering and external partners to diagnose issues and drive fixes. You will improve existing data flows and shape reusable data products that raise the bar on quality and speed. Accountabilities: Data Lifecycle Ownership: Assess new data feeds and business needs; define file specifications, source-to-target mappings, technical requirements and acceptance criteria; coordinate build, testing, business validation, deployment and operational handover to ensure trusted, usable outputs. Critical Feed Reliability: Oversee scheduled intake and delivery of specialty pharmacy, infusion, wholesaler and distributor data; monitor freshness, completeness and failures; lead recovery, reloads and timely stakeholder communications to protect downstream reporting and operations. Issue Investigation and Prevention: Use SQL in Snowflake to profile data, reconcile records and trace discrepancies across source files, ingestion, transformations and downstream outputs; determine root cause and implement durable fixes with automated checks to prevent recurrence. Trusted Data Product Development: Partner with data engineers to design reusable models and pipelines from raw ingestion to curated data products; define business rules, data quality controls, lineage and release validation so users can depend on consistent, well-documented data. Delivery and Prioritization: Maintain a clear Jira backlog across requests, enhancements, launches and incidents; assess impact and dependencies, drive requirements discussions, track decisions and guide cutovers, hypercare and post-release reviews for smooth, predictable delivery. Cross-Team and Vendor Connectivity: Collaborate with Trade and Distribution, Market Access, Commercial Operations, Decision Science, Reporting and Insights, CRM, IT and external data providers on definitions, interfaces, delivery schedules and ownership; translate technical issues into business terms and actions. Sustainable Operations and Compliance: Maintain mappings, data dictionaries, runbooks and validation evidence; mature monitoring and automation while applying access, privacy (including HIPAA) and contractual controls to sensitive commercial and patient-level data. Third-Party Data Aggregation Leadership: Serve as the business and operational lead for the external data aggregation partner, overseeing end-to-end aggregation across participating providers; establish delivery standards, governance, quality expectations and service levels; manage onboarding and feed changes; monitor performance; lead issue escalation and root-cause resolution; ensure aggregated outputs are accurate, timely, complete, compliant and fit for downstream use. Essential Skills/Experience: Education and experience: Bachelor’s degree in computer science, engineering, information systems, analytics, life sciences or a related field, or equivalent experience; at least 5 years in data operations, data engineering, data management or a related role. SQL and Snowflake: Strong hands-on SQL for complex joins, common table expressions, profiling, reconciliation and root cause analysis; practical Snowflake knowledge of schemas, tables, views, stages, roles, access controls, warehouses and query performance. Pipeline troubleshooting: Working knowledge of Python for validation or automation, Airflow or comparable orchestration for diagnosing schedules and failures, and dbt or comparable transformation tooling for models, tests, dependencies and deployment. Engineering and architecture: Ability to trace data end to end across files, ingestion, curated layers and downstream consumers; read existing code, technical designs, mappings and architecture diagrams; assess change impacts before release. Commercial data knowledge: Experience with pharmaceutical commercial data, including specialty pharmacy, patient services, specialty distribution or trade feeds, and an understanding of how quality and refresh timing affect business users. Delivery and collaboration: Experience writing requirements, acceptance criteria and validation evidence, managing concurrent work and incidents in Jira or a similar tool, and working independently with business, technology and vendor teams. Desirable Skills/Experience: Specialty and distribution data: Knowledge of patient referral, status, dispense and shipment data; wholesaler inventory and shipment feeds, including 852/867; and vendor corrections and reconciliations. Integration and release experience: Experience with SFTP, Amazon S3, Snowflake stages or secure sharing, Git based release practices and production deployment; familiarity with API or MuleSoft integrations. Broader commercial data: Familiarity with patient data, claims, CRM, HCP/HCO master data, roster and territory alignment, and vendors or platforms such as Veeva, IQVIA and Komodo. Rare disease experience: Experience in rare disease or specialty medicine markets, where small patient populations make specialty pharmacy and patient hub data especially important. Advanced analytics and AI enablement: Experience preparing reliable inputs for data models, patient or HCP analytics, scoring and alerts; validating model outputs and production data flows with Decision Science teams; or using AI assisted tools to improve data quality and operational troubleshooting. Influence and collaboration: Experience coordinating external vendors, supporting downstream Decision Science and reporting teams, and mentoring colleagues across teams. At Alexion, you will find a collaborative culture that encourages innovation and a diverse environment where your contributions are valued. You will have the opportunity to be at the forefront of rare disease research and make a meaningful difference in patients' lives. Ready to lead and inspire? Apply now and take the first step towards a fulfilling career at Alexion, AstraZeneca Rare Disease. ⠀ Annual base salary for this position ranges from 104,088.80 to 136,616.55. AstraZeneca is committed to providing fair and equitable compensation opportunities to all colleagues. Our compensation policies and practices have been designed to allow colleagues to progress through the salary range over time as they progress in their role. The range provided in this posting represents an offer pay range used in a majority of situations. The base pay offered will vary depending on multiple individualized factors, including the candidate's skills and experience, job-related knowledge, and other specific business and organizational needs. In some cases, offers outside the range may also be considered to address unique circumstances. In addition, our permanent positions offer an annual Variable Pay Bonus/Short Term Incentive opportunity as well as eligibility to participate in our equity-based long-term incentive program (if applicable to role). Benefits offered for permanent roles include a competitive Flex Benefits & Retirement Savings Program, 4 weeks’ paid vacation, and annual Personal Days. Fixed Term Contract/Temporary positions (excluding students) are offered a Contract Benefits Program. We are using AI as part of the recruitment process. This advertisement relates to a current vacancy.