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Protocol Intelligence
Data-driven signals on your job's competitivenessMumbai-based senior data engineering role with broad cloud/Spark/Python requirements attracts many qualified applicants.
Core data engineering skills are transferable across industries, with finance domain knowledge only as a plus.
Explicit 10+ years requirement plus mandatory cloud, Spark, Python, governance, and leadership increases shortlisting strictness.
Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and maintain scalable data platforms supporting financial research, analytics, automation, and AI solutions.
Lead and architect enterprise data platforms across 3–5 large-scale programs end-to-end, including data lakes, warehouses, lakehouses, and analytics products.
Provide technical leadership by mentoring 5-10 engineering team members, managing workstreams, and ensuring solutions meet scalability, security, governance, and operational resilience requirements.
Minimum Requirements
10+ years of experience in data engineering, architecture, migrations, or integration.
Delivered 5+ enterprise data projects involving cloud, lakehouse, or analytics platforms.
Strong skills in Python, SQL, Spark, cloud platforms (Azure/AWS/GCP), orchestration, and data modelling.
Work Experience Required: 10+ years in relevant data engineering roles.
Ideal Candidate Profile
Experienced in managing large-scale, enterprise data programs with a focus on financial data and analytics products.
Strong technical leadership capability including mentoring teams and overseeing stakeholder management.
Familiarity with financial domain knowledge (valuation, investment research) is a plus but not mandatory.