AVP – Data Engineer

We are seeking an experienced Assistant Vice President (AVP) to join our Asset management Data Engineering team at DWS in Bangalore, India. The successful candidate will be responsible for designing, developing, and supporting enterprise-scale data solutions that manage market data, security master data, trade data, position data, and investment analytics workloads across the Asset Management landscape.

The role requires strong technical expertise across data engineering, cloud data platforms like Snowflake and production support, combined with a solid understanding of financial instruments and investment management processes. The individual will collaborate with portfolio management, investment operations, risk, compliance, and technology teams to deliver scalable, reliable, and high-performance data solutions.

Your key responsibilities

• Design, develop, and maintain scalable data pipelines for market, trade, position, and reference data processing.
• Develop complex PL/SQL programs, database procedures, and performance tuning solutions.
• Build and maintain Python-based data integration and transformation frameworks.
• Develop Shell and/or Perl scripts to support automation, operational controls, and platform maintenance.
• Design ETL/ELT processes supporting large-scale financial data platforms.
• Facilitate ingestion via data shares and transformation of data into Snowflake-based data environments.
• Integrate data from external market data vendors, custodians, brokers, and internal applications.
• Design and support Kafka-based event-driven integration solutions.
• Implement data quality, reconciliation, and monitoring controls across critical data flows.
• Support enterprise scheduling using Control-M and/or AutoSys.
• Drive improvements in scalability, resilience, observability, and operational efficiency.
• Provide L3 support for critical production applications and data services.
• Lead root cause analysis and problem management activities.
• Support audit, compliance, and regulatory requirements relating to financial data.
• Ensure adherence to SDLC, release management, change management, and operational controls.
• Participate in disaster recovery, resilience, and operational readiness activities.
• Partner with business stakeholders across Investment Management, Operations, Risk, and Compliance.
• Support strategic data platform modernization initiatives and cloud transformation programs.
• Contribute to technical roadmaps and architecture decisions.

What we’ll offer you

• Best in class leave policy.
• Gender neutral parental leaves.
• 100% reimbursement under childcare assistance benefit (gender neutral).
• Sponsorship for Industry relevant certifications and education.
• Employee Assistance Program for you and your family members.
• Comprehensive Hospitalization Insurance for you and your dependents.
• Accident and Term life Insurance.
• Complementary Health screening for 35 yrs. and above.

Your skills and experience Mandatory Skills

• Strong PL/SQL development and database performance tuning experience.
• Advanced Python programming skills. (Data ingestion, validation and recon, automation and enrichment)
• Strong Shell Scripting and/or Perl Scripting experience.
• Experience with Snowflake Data Cloud and data shares.
• Strong knowledge of ETL, data integration, and data processing frameworks.
• Experience with enterprise scheduling tools such as Control-M or AutoSys.
• Experience working with Kafka and event-driven architectures.
• Strong SQL and relational database expertise.
• Experience supporting mission-critical production environments.

Asset Management Domain Knowledge

• Good understanding of the Asset Management industry.
• Experience with:
• Equities
• Fixed Income
• Derivatives
• Mutual Funds / ETFs
• Alternative Investments (desirable)
• Hands-on experience with:
• Trade Data
• Position Data
• Security Master Data
• Market Data Feeds
• Investment Reference Data

Experience

• 8-12 years of technology experience.
• 5+ years in Financial Services, Asset Management, or Capital Markets.
• Demonstrated experience delivering enterprise-scale data engineering solutions.
• Experience working in Agile delivery environments.
• Proven ability to leverage AI tools to enhance productivity, optimise workflows to solve business problems, while applying critical judgment to ensure responsible and ethical use of data and AI outputs.