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Specialized data leadership role without Tier-1 brand or remote reach.
Medium: core data engineering skills transferable, but enterprise/BFSI experience is preferred.
High: many mandatory technical skills and domain-specific delivery experience required.
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Lead and manage large-scale data engineering projects, including data lake build, migration, and PySpark optimization initiatives.
Own end-to-end project delivery: effort estimation, scoping, planning, team allocation, stakeholder management, and risk mitigation.
Provide technical leadership in designing modern data architectures (Data Lakes, Warehouses, Lakehouse) and ensure compliance with data governance, quality, security, and performance standards.
Proven hands-on experience managing end-to-end data projects including estimation, scoping, timelines, team allocation, and stakeholder management.
Strong technical expertise in Python, PySpark, Spark SQL, SQL, and ETL/ELT frameworks on cloud platforms (AWS, Azure, GCP), with preferred experience on GCP.
Experience delivering data lake implementation, migration, and large-scale data transformation projects.
Work Experience Required: Not explicitly mentioned in the JD.
Demonstrated ability to translate business requirements into scalable data solutions across cloud environments with focus on modern data technologies.
Experienced in driving agile delivery and managing enterprise-scale data modernization projects, preferably in Banking, Financial Services, or large enterprises.
Skilled in mentoring technical teams and enforcing best practices around data governance, security, performance optimization, and CI/CD DevOps processes for data platforms.