Lead Data Engineer (GenAI / LLM Applications)

What You’ll Be Doing

Design, develop, and maintain scalable software architectures and data pipelines that integrate with analytical and operational systems.

Write clean, reusable, and well‑tested Python code using frameworks such as Flask and related libraries.

Leverage AI‑assisted development tools, including GitHub Copilot and LangChain, to design, build, and integrate LLM‑powered solutions such as retrieval‑augmented generation (RAG) pipelines, intelligent agents, and automated workflows using AWS Bedrock or similar services.

Develop and optimize complex SQL across Oracle, MS SQL Server, PostgreSQL, and Snowflake, including procedures, functions, views, analytical functions, and dynamic SQL.

Design and implement ETL pipelines using Snowflake and related data processing technologies.

Implement scheduling and orchestration using Apache Airflow or similar workflow orchestration frameworks.

Establish and maintain data quality frameworks, versioning, and governance practices to ensure data reliability, integrity, and compliance.

Develop and maintain data architectures and models for both structured and unstructured data sources.

Troubleshoot production issues and drive continuous improvement in software quality, performance, and reliability.

Deploy, manage, and support solutions on AWS, including storage, compute, and pipeline services.

Create source‑to‑target mappings and support data and code migration initiatives.

Partner with stakeholders to gather requirements, translate business needs into technical solutions, and produce clear, well‑structured documentation.

Collaborate with product managers, analysts, and cross‑functional teams to deliver data‑driven insights and reporting using tools such as Plotly and Power BI.

What We Look For

Bachelor’s or higher degree in Computer Science, Information Technology, or a related technical field.

5+ years of professional experience in software engineering, data engineering, or data‑focused development roles.

Strong proficiency in Python, including frameworks and libraries such as Django or Flask, pandas, NumPy, Plotly, and ag‑Grid.

Strong SQL expertise with Oracle, MS SQL Server, PostgreSQL, and/or Snowflake.

Proven experience writing complex SQL, including analytical and window functions, subqueries, all join types, DML/DDL/TCL statements, CASE expressions, and performance tuning.

Working knowledge of cloud platforms, with a preference for AWS (S3, EC2, Secrets Manager, Bedrock, Lambda).

Experience using AI‑assisted development tools and frameworks such as GitHub Copilot and LangChain for building LLM‑powered applications and workflows.

Experience with Git‑based version control systems and CI/CD pipelines.

Familiarity with data modeling concepts for both structured and unstructured data.

Strong analytical thinking, problem‑solving abilities, and communication skills.

Willingness to work across all phases of the SDLC, including requirements gathering, design, development, deployment, and production support.

Preferred experience includes exposure to the clinical trial lifecycle or clinical data management, data visualization tools (Plotly, Power BI), front‑end technologies (HTML5, CSS3, JavaScript), collaboration tools (Jira, Confluence, Microsoft Teams), and hands‑on data analysis or data cleansing using programming languages, SQL, and Excel.

At Clario, our purpose is to transform lives by unlocking better evidence. It’s a cause that unites and inspires us. It’s why we come to work—and how we empower our people to make a positive impact every day. Whether you’re starting your clinical data career or building long‑term expertise, your work helps bring life‑changing therapies to patients faster.