Data Engineer - ETL/SQL (6-8 yrs)

Location : Bangalore

Notice period : Only Immediate joiners/15 days

Role : Data Engineer

Role Overview :

As a Data Engineer, you'll play a pivotal role in enabling efficient data access, analytics, and value generation across a global Science & Technology enterprise. You'll build and maintain data pipelines that bring data from diverse sources into a cloud-based analytics stack, working closely with business partners for data cleaning and preprocessing.

Partnering with Data Governance and Quality teams, you'll ensure data aligns with FAIR principles and implement reusable components and infrastructure to streamline future use-cases.

What We Offer :

- You'll be part of a dynamic team dedicated to delivering cutting-edge analytics solutions across a broad range of sectors.

- This role offers a unique opportunity to expand your expertise across various technical, scientific, and business domains, enhancing your Data Engineering skills within a project-based, multi-domain environment.

Qualifications :

- M.Sc./PhD/BE in Computer Science or related field with 6+ years of relevant experience.

- Proven experience with cloud platforms (e.g., Palantir, AWS, Hadoop) and data security best practices.

- Strong experience in Python, PySpark, R, and familiarity with additional programming languages (e.g., C++, Rust, Java).

- Skilled in designing ETL architectures for batch and streaming processes, database technologies (OLTP/OLAP), and SQL.

- Experience in Apache Spark, Hadoop ecosystem, and multi-platform/cloud setups (AWS, GCP, Azure).

- Knowledge of data governance, GxP data contexts, and familiarity with the Pharma value chain is a plus.

- Agile mindset with a proactive, hands-on approach and experience in leading teams.

Role Responsibilities :

- Work collaboratively with a Data Architect and Engineers to design and manage reliable, secure data pipelines, and cloud-based analytics architectures.

- Support data governance, gather requirements, and establish best practices with business and IT stakeholders to build a cohesive data framework for optimized decision-making and innovation.