Data Engineer (PySpark, ETL, AWS, SQL) | Pan India | 5 + Years | Immediate Joiners Only | Life Sciences / Pharma domain Experience Only

About the Role

Data Engineer

Key Responsibilities

• Design, develop, and maintain robust

  ETL pipelines

  using

  PySpark, Python, and AWS

  .
• Build, test, and optimize

  data management and processing systems

  for scalability and performance.
• Collaborate closely with

  solution architects and business stakeholders

  to translate data requirements into technical solutions.
• Ensure

  data architecture

  supports current and future business needs.
• Enhance

  data quality, reliability, and efficiency

  across systems and processes.
• Identify

  data acquisition and enrichment opportunities

  to increase business value.
• Develop and maintain

  data models

  that simplify system complexity and reduce operational costs.
• Contribute to

  Agile delivery

  processes through sprint planning, retrospectives, and reviews.
• Drive

  innovation and continuous improvement

  across the data engineering landscape.

Technical Skills Required

• PySpark

  ,

  Python

  ,

  SQL

  ,

  ETL development

• AWS Services:

  S3, Glue, Lambda, EMR, Redshift

• Data Pipeline design

  ,

  data modeling

  , and

  data transformation

• Experience with

  workflow orchestration

  and automation frameworks

Nice to Have

• Experience in

  Life Sciences / Pharma domain

• Exposure to

  Dremio

  ,

  NiFi ingestion

  , and

  Redshift

• Knowledge of

  BI tools

  such as

  Tableau

  or

  Power BI

• Understanding of

  data governance

  and

  compliance standards

Key Attributes

• Strong analytical and problem-solving mindset
• Excellent communication and collaboration skills
• Detail-oriented with a focus on performance and scalability
• Self-driven, proactive, and comfortable in

  Agile environments