Match Score
Against your primary resumeLogin to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Protocol Intelligence
Data-driven signals on your job's competitivenessLog in to see why each signal reads the way it does.
Job Description
Structured overview of role & requirementsAbout This Role
Establish and lead six foundational engineering frameworks for data pipeline lifecycle including DataOps, Data Quality, Observability, Modeling, Governance, and Pipeline Design Pattern library within the Finance Data Hub.
Drive adoption of these frameworks through documentation, enablement sessions, and enforcing conformance criteria to improve production quality and delivery velocity across data teams.
Lead modernization initiatives and integrate GenAI tools to enhance data engineering workflows, focusing on scalable solutions in Snowflake and automated CI/CD pipelines.
Minimum Requirements
B.E./M.Tech in Electrical, Electronics, or Computer Science or related field.
10+ years of experience in end-to-end delivery of enterprise-scale data pipelines with strong SQL and Python proficiency.
Deep hands-on expertise with Snowflake platform including data sharing, RBAC, row-level security, and query optimization.
Experience with GitHub-based CI/CD pipeline automation and designing branching/automated test strategies for data workloads.
Ideal Candidate Profile
Technical leader with experience setting standards and influencing engineering direction across cross-functional teams without direct managerial authority.
Proficient in designing reusable frameworks and enforcing data engineering best practices aligned with modern architectures like medallion and dimensional modeling.
Experienced in driving data engineering modernization and operational efficiency improvements with measurable impact, including leveraging GenAI tools for productivity enhancement.