Senior Data Engineer

Job Title : Senior Data Engineer

Experience : 5–8 years

Industry : Pharmaceutical / Biotechnology

Location : Bangalore

Employment Type : Full-Time

Overview

Our client – one of the largest data science companies – is seeking to hire a Senior Data Engineer with 5–8 years of hands-on experience in designing, building, and maintaining scalable, production-grade data platforms and pipelines. The ideal candidate will have a proven track record of delivering robust data solutions on cloud-native ecosystems, with strong client-facing engagement skills to gather requirements, present technical solutions, and drive stakeholder alignment. Demonstrated expertise in end-to-end data engineering lifecycle, cloud infrastructure, DevOps practices, and clear communication with business and technical audiences is essential. Experience in pharmaceutical, biotechnology, or medical device data environments is a strong advantage but not mandatory.

The ideal candidate will embrace the Company’s Decision Sciences Lifecycle and ways of working, acting as a trusted client-facing partner to enable long-term business, financial, and operational outcomes. They will design, implement, and support secure, performant data solutions using modern cloud tools, CI / CD pipelines, and a global delivery model. The role involves requirements elicitation, solution architecture presentation, pipeline development, performance optimization, and structured problem-solving in client engagements. Candidates must deliver high-quality, monitored, and well-documented solutions while leading offshore / nearshore team execution through mentoring, code reviews, and day-to-day delivery coordination.

Candidates must have hands-on, recent experience and strong proficiency in the following core data engineering domains :

Cloud-Native Data Pipeline Development & Orchestration

• Design and development of scalable ETL / ELT pipelines using Apache Spark (Databricks, Azure Synapse, AWS EMR), Apache Airflow, dbt, Prefect, or equivalent orchestration platforms
• Hands-on implementation of batch and streaming ingestion from diverse sources (databases, APIs, flat files, message queues, SaaS platforms, etc.)
• Advanced proficiency in Python (PySpark, pandas), SQL, and version-controlled pipeline development (Git) with CI / CD integration (GitHub Actions, Azure DevOps, Jenkins)
• Expertise with lakehouse formats (Delta Lake, Apache Iceberg, Hudi), schema evolution, partitioning, incremental processing, and performance tuning
• Implementation of data quality frameworks (Great Expectations, Monte Carlo, Deequ), lineage tracking, and automated testing
• Client-facing experience translating business requirements into technical designs and presenting pipeline architecture, runbooks, and monitoring dashboards

Cloud Infrastructure Management & Data Platform Engineering

Additional competencies considered strong advantages