Data Engineer Submission Data and Content Generation & Reuse (AIDCG) - Pharma R&D

Lead design, development, and maintenance of scalable, robust data pipelines and infrastructure for big-sized data engineering projects.

Build and optimize ETL/ELT processes and data storage solutions (data warehouses, data lakes) ensuring data quality, reliability, and monitoring.

Collaborate with data scientists, analysts, and business stakeholders to understand data needs and deliver scalable, reusable engineering solutions.

Proven experience managing complex, large-scale data systems and independently building ETL/ELT pipelines.

Proficiency in programming languages such as SQL, Python, Java, or Scala and expertise with Big Data tools (Hadoop, Spark).

Hands-on experience with at least one major cloud platform: AWS, Azure, or GCP.

Work Experience Required: Not explicitly mentioned in the JD.

Experienced in leading and executing complex data ingestion and processing projects at scale with strong problem-solving skills.

Able to engage and communicate effectively with both technical and non-technical stakeholders to translate requirements into scalable data solutions.

Skilled in developing reusable engineering components adhering to software engineering best practices (Git, CI/CD, testing, code reviews).