AVP – Data Engineer
Deutsche Bank is hiring an AVP – Data Engineer. Level rates it ; you can apply on Deutsche Bank.
Level's read on this job
- Level rates this data engineer role Little AI ●○○○: aI is not part of the work.
- Level classifies it as a senior role.
- Level lists 1,100+ other open roles at Deutsche Bank.
- The role was posted in the last few days.
AI in this role
Job Description:
Job Title: AVP – Data Engineer
Location: Bangalore, India
Role Description
We are seeking an experienced Assistant Vice President (AVP) to join our Asset management Data Engineering team. 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.
What we’ll offer you
As part of our flexible scheme, here are just some of the benefits that you’ll enjoy,
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 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.
Your skills and experience
Mandatory Skills
Technical 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
Good to Have
Microservices development experience.
Experience with cloud platforms (Azure preferred).
Experience with monitoring and observability tools.
Understanding of distributed application architectures.
Knowledge of modern data platform technologies and streaming architectures.
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.
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.
How we’ll support you
Training and development to help you excel in your career.
Coaching and support from experts in your team.
A culture of continuous learning to aid progression.
A range of flexible benefits that you can tailor to suit your needs.
About us and our teams
Please visit our company website for further information:
https://www.db.com/company/company.html
We at DWS are committed to creating a diverse and inclusive workplace, one that embraces dialogue and diverse views, and treats everyone fairly to drive a high-performance culture. The value we create for our clients and investors is based on our ability to bring together various perspectives from all over the world and from different backgrounds. It is our experience that teams perform better and deliver improved outcomes when they are able to incorporate a wide range of perspectives. We call this #ConnectingTheDots.
How we rate this
AVP – Data Engineer at Deutsche Bank rates 15 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
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Pay
- Typical data engineer job
- $150k
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