Associate Director, Data Analytics

IQVIA•Wayne, PA

1d•Remote

About The Position

The Associate Director of Data Analytics provides technical and people leadership to design, build, and scale data and analytics solutions that support regulatory compliance, operational performance, and strategic decision-making across healthcare and life sciences. This role owns end-to-end delivery across multiple workstreams, establishes repeatable engineering and governance standards, and partners with Product, Engineering, Sales, and client stakeholders to grow and modernize analytics capabilities. This leader is expected to operate effectively in a matrix environment, balance competing priorities, and communicate clearly and diplomatically with senior internal and client leaders while driving measurable outcomes.

Requirements

Bachelor’s degree in a relevant field or equivalent experience.
Proven people leadership and delivery ownership in a matrix environment.
Strong SQL + Python (or equivalent) delivering production-grade pipelines and automation.
Experience with cloud data architectures and modern platforms (Azure/AWS; Snowflake/Databricks or equivalent).
Strong stakeholder communication/presentation; calm, assertive, and diplomatic.
Business acumen: planning, prioritization, and financial awareness.

Nice To Haves

Experience leading data governance / metadata / lineage / stewardship operating models.
Healthcare/life sciences exposure where compliance/auditability are critical.
Experience delivering governed semantic models and self-service analytics.
RFP/orals and client solutioning leadership.

Responsibilities

Lead, hire, coach, and retain a high-performing team; set goals, provide feedback, and drive career development.
Establish operating rhythms and delivery governance (planning, prioritization, design reviews, release readiness, incident/defect triage) to ensure predictable execution and quality.
Drive a culture of accountability, documentation, and continuous improvement across teams and partners.
Own the end-to-end lifecycle of data and analytics products—from discovery through build, release, adoption, and operations—delivering reusable capabilities with measurable business impact.
Build product-grade data foundations (canonical models, curated datasets, semantic layers, governed metrics) and reference data (e.g., MDM/hierarchies) to ensure consistency and reuse.
Operationalize cloud data products (Azure/AWS) using strong engineering practices: Git, CI/CD, automated testing, documentation, and runbooks.
Deliver scalable pipelines, automations, and accelerators for compliance/regulatory reporting and operations at scale using Python, SQL and orchestration (Airflow/ADF or equivalent).
Provide governed analytics experiences (dashboards, self-service datasets, alerting) for compliance KPIs, variance analysis, and executive decisioning.
Embed healthcare-grade data trust: definitions/lineage, access controls, privacy-by-design (PHI/PII where applicable), and data quality monitoring with root-cause remediation.
Incorporate agent-enabled capabilities where they improve usability and speed-to-insight (e.g., agent-assisted Q&A, summaries/insights, guided workflows) using enterprise-supported approaches and enablement resources.
Own scope, milestones, acceptance criteria, dependencies, and risk/issue management across multi-workstream initiatives to ensure on-time/on-budget outcomes.
Translate regulatory and business changes into actionable delivery plans; communicate tradeoffs, decisions needed, and mitigation plans to senior stakeholders.
Define measurable success criteria and track outcomes (e.g., reduced manual effort, improved audit readiness, increased adoption of governed data products).
Own or co-lead RFPs: solution strategy, win themes, response authoring, compliance matrices, and executive summaries; partner with BD/Sales to shape proposals.
Lead client demos/pilots/orals; contribute reusable assets and accelerators that increase speed-to-value and differentiation.
Build and maintain senior client relationships; identify expansion opportunities and translate them into scalable offerings and roadmap items.
Maintain the analytics/platform roadmap and architecture guardrails to drive modernization, interoperability, security, and scalability.
Evaluate and adopt emerging technologies (including AI/ML and agentic patterns) where they measurably improve delivery efficiency, insight generation, or customer outcomes.