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Senior Bangalore data role with broad, popular stack increases competition despite lesser-known employer.
Core data engineering skills are highly transferable; life-sciences knowledge is only a bonus.
Explicit 8+ years plus many mandatory data engineering technologies, governance, and leadership requirements.
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Design, build, and optimize scalable batch and real-time data pipelines using PySpark, Python, and SQL across cloud platforms (AWS, Azure, GCP).
Lead architecture design, define standards, develop reusable frameworks, and enforce data engineering best practices including data quality and governance.
Mentor data engineering teams, collaborate cross-functionally, and manage complex data workflows using tools like Airflow and CI/CD pipelines.
8+ years of experience building production-grade data engineering solutions.
Strong proficiency in Python, PySpark, advanced SQL, and cloud data platforms (Databricks, Snowflake, Redshift, BigQuery).
Experience with batch and real-time data systems (Spark Streaming, Kafka, Kinesis) and workflow orchestration (Airflow).
Knowledge of data governance, compliance (GDPR, HIPAA), and experience establishing coding, testing, and deployment standards.
Experienced technical leader capable of setting engineering standards, mentoring teams, and driving scalable data platform development.
Deep expertise in modern cloud-based data warehouse and lake architectures with strong operational and optimization skills.
Comfortable working in Agile environments collaborating with Data Scientists, Analytics Engineers, QA, and DevOps teams.