Senior Data Engineer
Summary
Leads the 'Data Tower' of enterprise-scale data transformation programs for asset, investment, and wealth management clients — managing global delivery teams, defining data strategy and lakehouse architecture, and driving delivery on Databricks, dbt, Azure and AWS. Based in Bangalore, Hyderabad, Chennai, or Kolkata.
Work Location: Bangalore, Hyderabad, Chennai, Kolkata
Must Have Technical/Functional Skills
Required Experience
· 8-10 years in Data & Analytics programs.
· 5+ years leading enterprise-scale data transformation initiatives.
· Proven experience managing global delivery teams.
· Hands-on experience with Databricks, DBT
· Experience working with Asset Management, Investment Management, or Wealth Management
organizations.
· Strong experience in Agile, Scaled Agile, or Hybrid delivery models.
Roles & Responsibilities
Key Responsibilities
Program Leadership & Governance
· Lead the Data Tower within enterprise-wide EDO transformation programs.
· Define and execute data strategy aligned with business and technology objectives.
· Manage multiple delivery teams across data engineering, analytics, governance, and cloud
platforms.
· Drive program planning, budgeting, resource management, and delivery governance.
· Establish KPIs, SLAs, risk management frameworks, and program health reporting.
· Present program status and strategic recommendations to C-level stakeholders.
Data Platform & Architecture Leadership
· Lead the design and implementation of modern data platforms leveraging:
· Databricks Lakehouse Architecture · Azure Data Platform · AWS Data Services · DBT Transformation Framework · Define scalable architecture patterns for batch, streaming, and real-time analytics workloads. · Establish enterprise data standards, best practices, and reusable frameworks. Asset Management Domain Enablement · Drive data initiatives supporting: · Portfolio Management · Investment Research · Trading & Order Management · Performance & Attribution · Risk Analytics · Compliance & Regulatory Reporting · Client Reporting · Security Master & Reference Data Management · Collaborate with business stakeholders to define data products and business capabilities. Data Engineering Leadership · Lead development of enterprise-grade data pipelines using Databricks and cloud-native technologies. · Define ELT/ETL frameworks utilizing dbt and modern data engineering methodologies. · Ensure high-quality delivery through automation, CI/CD, testing, and observability practices. · Optimize data processing costs and performance across cloud environments. Cloud & Platform Management · Provide leadership across Azure and AWS cloud ecosystems. · Define cloud migration and modernization strategies. · Ensure platform security, resiliency, scalability, and governance. · Drive FinOps practices for cloud optimization and cost management. Stakeholder Management · Partner with: · Chief Data Officers · Data Governance Leaders · Portfolio Management Teams · Enterprise Architects · Compliance & Risk Functions · Technology Leadership ·
Serve as the single point of accountability for Data Tower delivery. --- · Required Technical Skills · Databricks · DBT