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Mid-level role, metro location, broad required skillset, and reputable global employer increase competition.
Data engineering skills transfer across industries, though life-sciences domain experience is a beneficial differentiator.
Explicit 3–5 years plus mandatory Databricks, Glue, SQL, Spark, and Python makes shortlisting highly strict.
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Maintain, support, and enhance PDS data platforms, ETL pipelines, and analytics/UI applications using AWS Glue, Databricks, DBT, and React.
Ensure high availability and reliability by analyzing and resolving production incidents in line with SLAs.
Drive operational efficiency through automation, monitoring, data quality validation, and collaboration with cross-functional teams.
3-5 years of experience in operations, production support, and process optimization.
Hands-on experience with AWS Glue, Databricks, SQL, SPARK, Python, and data engineering tools such as Airflow.
Degree preferred in Computer Science, Physics, Math, Pharmaceutical Science, or Engineering.
Experience with version control (Git, SVN), Agile methodology, and familiarity with cloud infrastructure and monitoring tools.
Experienced in managing production support in cloud-based data platforms, focusing on operational stability and scalability.
Comfortable working with global and cross-functional teams, including offshore technical groups.
Familiar with modern AI technologies and development tools relevant for analytics operations in life sciences domain.