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Tier-1 employer, common data-engineer role in metro hubs with broad Databricks/AWS requirements increases applicant competition.
Highly domain-specific Databricks/AWS data platform skills restrict cross-industry transferability.
Explicit 7+ years and mandatory Databricks, AWS, and AI-assisted data engineering experience required.
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Design, build, and operate scalable batch and streaming data pipelines using Databricks Lakehouse platform with focus on reusable data engineering frameworks and automation.
Own reliability, governance, security, and cost management of data engineering pipelines and shared platform components.
Drive architectural decisions, implement AI driven automation for workflows optimization, and collaborate to standardize data frameworks and patterns.
7+ years of strong Data engineering experience including AI assisted development.
Hands-on experience with AWS, Databricks ecosystem (including Fivetran ingestion, Acceldata observability), and Python programming.
Bachelor's degree in Computer Engineering, Computer Science, Information Systems or related field with 7+ years IT work experience.
Experience designing scalable data pipelines, reusable frameworks, and implementing automation in data workflows.
Experienced in designing and operating enterprise-grade data platforms with solid understanding of data modeling, schema evolution, and query performance trade-offs.
Skilled in building AI-assisted automation for data quality monitoring, pipeline observability, cost and performance optimization.
Capable of driving cross-team adoption of shared frameworks and automation while ensuring security, compliance, and platform reliability.