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Metro location and broad technical stack increase applicant density, though seniority reduces competition.
Requires product-company experience and deep data engineering domain knowledge, limiting cross-industry transferability.
Explicit 10+ years, required leadership experience, and broad mandatory data tech stack enforce strict filtering.
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Lead design, development, and maintenance of scalable data engineering infrastructure and pipelines (batch and real-time).
Act as SME and architect data migration solutions from on-premises to cloud-based PaaS, focusing on multi-terabyte databases and data warehousing across multiple technologies.
Provide technical leadership, establish best practices, mentor junior engineers, collaborate with stakeholders, and ensure data security, compliance, and governance.
Bachelor's degree in Computer Science, Engineering, or related field (Master's preferred).
10+ years in data engineering roles with at least 2 years in technical leadership positions.
Mandatory experience working in product-based companies.
Experience with cloud platforms (AWS/Azure/GCP), big data technologies (Hadoop, Spark, Kafka), data warehousing, data modelling, ETL design and optimization.
Experienced in leading data/analytics engineering teams with ability to translate business requirements to technical solutions.
Strong expertise in data migration, data modelling (dimensional, relational, NoSQL), and cloud-based data architectures (data lake, lakehouse, data mesh/fabric).
Practiced in agile development, hands-on with programming (Python, SQL, Java, Scala), CI/CD, and monitoring tools; able to guide large-scale data infrastructure projects with cross-functional collaboration.