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Tier-1 brand, metro location, mid-level popular Data Engineer title, and broad cloud/Databricks requirements increase competition.
Core data engineering skills are highly transferable across industries, so background sensitivity is low.
Explicit 5+ years Databricks/Hadoop/Scala and cloud mandates make shortlisting highly selective.
Own design, implementation, and maintenance of secure, scalable data infrastructure across AWS/Azure and data centers.
Manage data platforms including data lake, warehouse, stream processing, unified query engine, analytics extracts, dashboards, and visualizations.
Ensure SLA and KPI adherence, scale data systems according to business needs, and mentor engineers in software engineering best practices.
Minimum 5+ years of work experience with Databricks on Azure Cloud.
Hands-on expertise in Hadoop and Scala for at least 5+ years.
Proficiency in at least one programming language: Python, Scala, or SQL.
Knowledge of end-to-end data analytics workflows and professional experience with Databricks; knowledge of AWS or Azure cloud platforms mandatory.
Strong ownership mentality with good sense of urgency and self-prioritization skills.
Experienced in data engineering including DevOps & DataOps workflows in dynamic, consultative environments.
Capable of mentoring peers and designing systems with monitoring, auditing, reliability, and security integrated.