Establish and enforce data engineering best practices (scalable pipeline patterns, testing, observability, recovery, and documentation).
Ensure operational excellence across Databricks/S3 pipelines powering BI, web analytics, and 3rd‑party competitive datasets.
Ensure quality control and release readiness
Own operational health of MSO ingestion and processing—logging, monitoring, DQM validation, publish/stitch status tracking, and automated notifications when feeds or taxonomy inputs fail.
Own release operationalization by maintaining runbooks, validation notebooks/checklists, and production observability artifacts (ingestion logs, error traces, alert routing) so deployments are traceable, recoverable, and supportable.
Drive Agile Ops, Governance, and Predictable Delivery
Own MSO’s Agile operating model across BI and Data Engineering, ensuring clear backlogs, prioritization, sprint discipline, and dependency management.
Establish delivery governance that enables predictable releases, transparent trade‑offs, and proactive risk management.
Ensure strong KPI traceability, documentation standards, and release discipline across all BI and data assets.
Executive Stakeholder & Cross‑Functional Leadership
Serve as a senior leader and escalation point across MIO, brand teams, Decision Sciences, engineering, and vendors.
Influence prioritization and investment decisions by aligning MSO capabilities with commercial and strategic needs.
Build strong partnerships with senior stakeholders by consistently delivering trusted data and insights.
People & Org Leadership
Lead, develop, and scale BI Managers, Data Engineering Managers, and their teams.
Set clear expectations for ownership, quality, and leadership behaviors across the org.
Build a high‑performance culture focused on accountability, continuous improvement, and business impact.
Thrive | What you can expect
As we work to develop treatments that take care of others, we also work to care for our teammates’ professional and personal growth and well-being.
Basic Qualifications
Master’s /Bachelor's degree or PhD in Data Engineering, Information Systems, or a related quantitative field.
12 - 15 years of experience in media analytics, digital data ops, or MarTech roles, with at least 3+ years of people management.
Deep understanding of digital media ecosystems and hands-on experience with campaign data flows from ad platforms to dashboards.
Demonstrated success designing and scaling data platforms on AWS, Databricks, or equivalent cloud infrastructure.
Strong delivery leadership skills and comfort managing stakeholders across marketing, engineering, and external vendors.
Preferred Qualifications
Background in the pharma industry or other regulated domains with compliance requirements for media data.
Experience managing vendor ecosystems, campaign data pipelines, and reporting operations across multiple brands or markets.
Familiarity with campaign activation tools (e.g., Salesforce plugins, Datorama, SFMC) and taxonomy/tagging standards.
Strategic mindset with the ability to lead capability building while maintaining operational stability.
Strong written and verbal communication skills; experience presenting data strategy to executive audiences.
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