Data Engineer ::

Title : Data Engineer
Location : Remote

Must Have

• 2 4 years of experience in data engineering or analytics engineering.
• Strong SQL; experience with relational modeling, stored procedures, and performance tuning.
• Hands-on with Azure data services (e.g., Azure Databricks, ADLS; Azure Data Factory or Synapse pipelines a plus).
• Experience building Power BI datasets, DAX measures, and row-level security; comfortable with Power Query/M.
• Scripting in Python preferred; familiarity with Spark/Databricks is a plus (willingness to learn required).
• Version control with Git; exposure to CI/CD concepts on Azure.
• Excellent communication and teamwork in a fast-moving, cross-functional environment.
• Pharmaceutical domain exposure (e.g., R&D, clinical/preclinical, lab/assay data) is a strong plus.
• Strong analytical and problem-solving skills with attention to detail
• Ability to work independently while maintaining strong collaboration with team members

Key Responsibilities

• Pipelines, Modeling, and BI Enablement
• Build and maintain ETL/ELT pipelines across relational databases (e.g., SQL Server, Postgres, Oracle) and Azure storage (ADLS).
• Develop clean, well-modeled datasets for analytics and self-service BI; create and manage Power BI datasets, reports, and refresh schedules.
• Support and enhance existing pipelines on our Azure digital platform, including basic Databricks/Spark tasks with guidance.
• Implement data quality checks, documentation, and observability for reliable production workflows (e.g., Azure Monitor/Log Analytics).
• Collaborate with scientists, analysts, and engineers to translate requirements into scalable Azure data solutions.
• Contribute to version control practices (Git) and CI/CD using Azure DevOps or GitHub Actions.
• Participate in standards alignment with enterprise data engineering and platform teams.