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Mid-level data engineering role in Mumbai with common Databricks/Kafka skills attracts moderate competition.
Specialized data platform skills (Databricks, Kafka, AWS) transfer across industries but require specific tooling experience.
Mandated 6-8 years and specific Databricks, Airflow, Kafka, AWS expertise makes filtering strict.
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Design, build, and operate reliable, scalable data pipelines and cloud-native data platforms primarily on AWS using Databricks, Airflow, Kafka, and distributed processing frameworks.
Make architectural and data modeling decisions for enterprise data environments, optimizing for production readiness including security, testing, observability, and cost-efficiency.
Support production systems by troubleshooting, improving performance, reliability, and data quality, and mentor junior engineers while contributing to shared standards.
6-8 years of hands-on data engineering experience.
Strong skills with Databricks, Airflow, Kafka, Python, Java, Spark, and advanced SQL.
Experience operating at significant scale and complexity in enterprise environments with proven architecture and data modeling decisions.
Hands-on experience building and running batch and streaming data pipelines on AWS or similar cloud-native platforms.
Experienced in making high-level architectural and data modeling decisions in complex enterprise settings.
Skilled in working with modern data platforms and solutions operating at scale, primarily on AWS and Databricks ecosystems.
Has mentoring experience and contributes to technical standards, supporting cross-functional collaboration with data scientists, analysts, and AI engineers.