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The Giant Bullseye

ETL Lead

The Giant Bullseye, Saint Louis, Missouri, United States

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Job Description

Job Description

About the Role

We are looking for a seasoned

ETL Lead

to drive data integration and warehousing initiatives for a leading pharmaceutical organization. This role combines deep technical skills in

Informatica and Snowflake

with a strategic mindset to deliver business value through scalable data engineering solutions. You will serve as both a hands-on technical leader and a consultative partner to business stakeholders.

Key Responsibilities

Lead the architecture, design, and development of ETL solutions using

Informatica PowerCenter and IICS .

Build scalable, high-performance data solutions on the

Snowflake Data Cloud .

Design robust

dimensional data models , ensuring alignment with business reporting needs.

Act as a trusted advisor to business leaders, uncovering opportunities for data-driven decision-making.

Translate complex, unstructured problems into scalable, maintainable data pipelines.

Manage and mentor a team of data engineers to deliver integration projects efficiently.

Drive

legacy system migrations

and consolidation efforts into Snowflake.

Collaborate with analytics, business, and compliance teams to define data requirements and ensure delivery.

Optimize data pipelines and warehouse performance using partitioning, indexing, and tuning techniques.

Deliver clear documentation and presentations for both technical and executive stakeholders.

Required Skills & Qualifications

8+ years of hands-on experience in

ETL/data engineering , with deep expertise in

Informatica (PowerCenter & IICS) .

Strong

SQL programming

and query optimization skills.

Proven track record designing and scaling solutions in

Snowflake .

Expert in

data warehousing concepts

and

dimensional modeling .

Pharma industry experience required; familiarity with

IQVIA, Komodo, Veeva datasets

highly preferred.

Strong communication and stakeholder engagement skills.

Demonstrated ability to lead discussions on

data strategy and business value generation .

Comfortable with

Agile delivery environments , shifting priorities, and ambiguity.

Preferred Qualifications

Strong background in the

life sciences or pharmaceutical industry , ideally with exposure to enterprise environments such as Bristol Myers Squibb, Abbott, Pfizer, or similar organizations. Understanding of FAIR data principles and data standardization in biomedical research.

Knowledge of clinical data standards (e.g., CDISC, SDTM).