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Tier-1 brand and metro location but senior specialized cloud-data role so moderate competition.
Skills are transferable across industries, though financial-services experience is preferred.
Explicit 10–15 years plus mandatory AWS/Databricks, Python, and ETL experience enforces strict technical filters.
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Design, develop, and manage high volume cloud data ingestion and integration pipelines using AWS and Databricks platforms.
Develop and implement cloud infrastructure and tools for data lake solutions including deployment, testing, and production support.
Own issue diagnosis, resolution, and compliance with coding, security, and privacy standards in cloud data engineering projects.
10-15 years of work experience in data engineering with hands-on cloud experience, preferably in Financial Services.
Proficiency in AWS Cloud Data Engineering and Databricks platform with expertise in data modeling and database design.
Strong coding skills in Python, PySpark, SQL, Java, and PL/SQL; experience with Oracle RDBMS and ETL pipelines.
Work Schedule: Hybrid; strong knowledge of cloud security (IAM roles, policies, encryption) and CI/CD tools like GIT, Jenkins, Autosys/Control-M.
Experienced in building and managing cloud-based database engineering platforms at scale with financial services background.
Ability to lead technical design, development, and deployment of cloud data lake solutions within fast-moving, elite development teams.
Familiarity with advanced DevOps practices, data governance tools (e.g., Collibra) and strong operational ownership for production environments.