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Tier-1 brand, metro location, mid-level generalist data role, and in-demand Databricks/Azure skills increase competition.
Core data engineering skills are transferable, though financial domain experience gives an advantage.
Explicit 5+ years and mandatory Databricks, Hadoop, Scala and cloud skills make filters strict.
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Design, implement, and maintain secure and scalable data infrastructure across AWS/Azure and Data Center environments.
Own SLA compliance and system KPIs, ensuring high availability, throughput, data consistency, security, and privacy in data analytics tooling.
Collaborate cross-functionally to scale data systems, work on data lake/warehouse, and mentor engineers while promoting software engineering best practices.
Minimum 5+ years experience with Databricks using Azure Cloud and hands-on expertise in Hadoop and Scala.
Proficiency in at least one public cloud platform: AWS or Azure (knowledge of GCP is not sufficient alone).
Strong programming skills in Python, Scala, or SQL and knowledge of end-to-end data analytics workflows.
Work Experience Required: Minimum 5+ years Databricks and cloud data engineering experience explicitly mentioned.
Demonstrates strong end-to-end ownership with urgency and effective self-prioritization in a dynamic, consultative environment.
Experienced in designing systems with monitoring, auditing, reliability, and security baked-in.
Capable of mentoring others and advancing software engineering best practices within a large organization focused on scalable data analytics solutions.