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Tier-1 brand, metro location, mid-level data engineer title and broad skills create high candidate competition.
Data engineering skills are transferable, but platform-specific Databricks/Snowflake and GenAI needs increase domain specificity.
Explicit 6+ years plus mandatory Databricks, Snowflake, PySpark, AWS and GenAI skills enforce strict shortlisting.
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Lead design and implementation of AI-driven solutions including agentic AI and Generative AI workflows, integrating them with existing data platforms.
Develop and refactor production-grade Python and PySpark data pipelines and APIs, optimizing for scalability and maintainability in cloud environments.
Manage and optimize analytics platforms (Databricks, Snowflake) and cloud ETL pipelines (AWS Glue), ensuring performance, governance, and security compliance.
6+ years experience in Data Engineering or Analytics Engineering roles.
Strong hands-on expertise with Generative AI, LLMs, and agentic AI orchestration.
Advanced Python development skills including experience with Flask or FastAPI, and strong proficiency in PySpark.
Expert-level skills in Databricks, Snowflake, AWS Glue, and AWS cloud-native data pipeline architectures.
Experienced in architecting AI-led data transformations and operationalizing GenAI workloads in enterprise cloud platforms.
Able to lead cross-functional technical solutions involving AI, Python engineering, distributed processing, and database administration.
Comfortable managing complex analytics environments with a focus on cost, security, observability, and automation in regulated or enterprise settings.