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Tier-1 brand, mid-level generalist Data Engineer role with metro location and common skills increases competition.
Data engineering skills (Databricks, Scala, cloud) are broadly transferable across industries.
Explicit 5+ years and mandatory Databricks/Hadoop/Scala/Azure requirements create high shortlisting strictness.
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Design, implement, and maintain secure, scalable data infrastructure across AWS/Azure and data centers, including data lakes, warehouses, and stream processing.
Own internal and external SLAs, monitor system KPIs, and ensure high availability, throughput, consistency, security, and privacy of data systems.
Mentor engineers, promote best software engineering practices, and develop scalable solutions for diverse business data needs, focusing on data analytics tooling.
Minimum 5+ years of hands-on experience with Databricks on Azure Cloud and Hadoop with Scala.
Proficiency in at least one programming language: Python, Scala, or SQL.
Experience with public cloud platforms AWS or Azure; practical knowledge of end-to-end data analytics workflows and DevOps/DataOps in Data Engineering.
Work Experience Required: Minimum 5+ years Databricks experience; Certifications in Azure/AWS, Hadoop, Scala, or Databricks are good to have but not mandatory.
Experienced in managing complex data platforms combining cloud services (AWS/Azure) and on-premises data centers.
Demonstrates strong ownership with a results-driven approach to prioritize effectively under deadlines.
Familiar with full software development lifecycle (SDLC), Agile methodologies, and mentoring engineering teams on best practices.