Senior Director, AI - Data/Systems Engineering & Management

Job Description

Job Description:

Insight Global is seeking a Senior Director to join a leading biotech company and shape how data and information solutions enable the delivery of life-changing medicines to patients. This is a hands-on technical leadership role, responsible for architecting solutions, evaluating vendor platforms, occasionally writing code, and leading a high-performing engineering team. This leader will own the data engineering capability across the R&D and manufacturing value chain.

This role serves as the primary technology interface for Data, AI, and Engineering across Research, Early Development, and Technical Operations & Quality. You will act as both a strategic and hands-on bridge between the enterprise data platform and the technical business functions that rely on it, ensuring data, AI-enabled solutions, and engineering standards are deeply embedded into how these functions operate and innovate.

You will lead a team of 10 data engineers and data management professionals and be directly accountable for all engineering delivery in this space. You will be responsible for growing the team by hiring roughly 8 more individuals. You will build and operate data infrastructure, pipelines, and governance capabilities on or adjacent to the Snowflake Lakehouse, enabling manufacturing analytics, research data integration, quality intelligence, and supply chain planning, in close partnership with IT Vertical Leadership for Research & Early Development (ReDev) and Technical Operations & Quality (TOQ).

Responsibilities:

• Own the data platform and systems engineering capability for ReDev & TOQ, delivering reliable, scalable, and GxP-compliant data services.

• Architect and modernize end-to-end data integrations across lab, manufacturing, quality, and enterprise systems using a modern data stack. (Fivetran, dbt, Snowflake, Astronomer, semantic layers).

• Lead the transition from legacy batch ETL and point-to-point integrations to automated ingestion (e.g., Fivetran), continuous loading (Snowpipe), and governed Lakehouse architectures.

• Serve as the accountable technical authority-setting architectural standards, reviewing designs and vendor proposals, and guiding complex integrations across MES, ELN, LIMS, SAP, and QMS.

• Ensure data pipelines, models, and semantic layers (Python, SQL) support analytics, regulatory submissions, batch release, and advanced use cases including AI/ML.

• Implement CI/CD and infrastructure-as-code for data platforms using GitHub Actions, Terraform, and dbt testing, with strong observability and data quality controls.

• Establish strong data governance, lineage, master data, and validation practices to meet regulatory and quality requirements.

• Build, mentor, and lead a high-performing data engineering team, owning delivery, quality, and continuous improvement.

• Partner closely with IT and business leaders as a true "two-in-a-box" owner of outcomes.

• Champion a product-oriented, value-driven operating model-and love great engineering.

Benefit packages for this role will start on the 1st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to [email protected] learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy:

Skills and Requirements

Must Haves:

• 10+ years building production data platforms and pipelines.

• 5+ years technical leadership experience.

• Experience with ELT/ETL, lakehouse architectures, streaming, cloud-native platforms.

• Expert Snowflake experience: data modeling, performance tuning, Snowpipe, data sharing.

• Strong Databricks experience for analytics and ML workloads.

• Hands-on with Fivetran, Airflow/Astronomer, dbt, and data observability tools (e.g., Monte Carlo).

• Expert SQL and Python; production-quality code standards and reviews

• Manufacturing and enterprise system integration experience, including SAP (PP, MM, QM) and MES.

• Enterprise data architecture ownership: technical specs, integration patterns, vendor due diligence.

• Data system validation and risk-based CSV experience in regulated environments.

• Compliant data systems: audit trails, access controls, e-signatures, data integrity, validated pipelines.

• Delivery of complex, concurrent initiatives in regulated, data-intensive environments.

• Strong executive communication: data concepts and lineage to business, manufacturing, and quality leaders. - Experience with RNAi therapeutics, biologics, or similar modalities.

• Experience with Veeva Vault (QMS, RIM), electronic lab notebooks or CTMS platforms.

• Background in data mesh, domain-oriented data products, or decentralized data architectures.

• Experience transitioning organizations from project-based delivery to product-oriented operating models.

• Knowledge of scientific data formats and standards (CDISC, SDTM, ADaM).