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Remote, popular data-engineer role with broad skills and metro location creates high candidate competition.
Specialized cloud and Databricks skills moderately limit cross-industry transferability.
Explicit 8+ years, leadership, and specific Azure/Databricks/Spark requirements drive high shortlisting strictness.
Lead the design, development, deployment, and maintenance of scalable, efficient data and analytics platforms, focusing on ETL/ELT pipelines and data processing solutions.
Implement data governance, quality, monitoring, and security frameworks to ensure compliant and reliable data availability for analytics and business use.
Provide technical leadership including mentoring, technical decision-making, and collaboration with stakeholders to deliver enterprise-wide data solutions aligned with business objectives.
8+ years of hands-on experience in Data Engineering, Big Data, or related disciplines with 3+ years leading technical teams or projects.
Strong expertise in Azure cloud data services (Databricks, ADLS, Synapse), Apache Spark, Python, Scala, SQL, and building large-scale ETL/ELT pipelines.
Bachelor’s degree or equivalent qualification in Computer Science, IT, Engineering, Data Science, or related field; relevant professional experience may substitute.
Experience implementing CI/CD pipelines, DevOps practices, and working within Agile development methodologies.
Experienced in leading large-scale, enterprise cloud-based data engineering initiatives with proven ability to balance strategic architecture and hands-on technical execution.
Strong background in scalable distributed data processing, performance optimization, and managing data lakehouse architectures with deep Azure ecosystem knowledge.
Proficient in collaborating cross-functionally with technical and business stakeholders to translate requirements into actionable, compliant, and high-quality data solutions.