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Investment & Asset Management · 1001 to 5000 Employees · Frankfurt am Main, Germany
1 open role1 posted in 7d1 in 30d
Work-life balance 3.7Compensation & benefits 3.2Culture & values 3.2
Hiring: Engineering
What employees say
+ Work life balance, leave policy, working hrs
− Slow decision making, inefficient processes
More reviews on the company profile.
Interview experience · Vice President
There were about 4 rounds including the final HR. Initial one was a tech round followed by a tech and managerial round. That was followed by a culture fit round by the MD and then finally the HR
Average difficulty · Pune · 5 reports
More interview insightsJob description
Overview
Job Title: AVP - Data Engineer
Responsibilities
- 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.
- 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
- 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.
Qualifications
- 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.
- 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
- 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.
- 8-12 years of technology experience.
- 5+ years in Financial Services, Asset Management, or Capital Markets.
- Demonstrated experience delivering enterprise-scale data engineering solutions.
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Job application FAQ
Last updated 28 October 2026
- How do I apply for AVP - Data Engineer | Bangalore, IN at DWS Group?
- Open this job on Feedback AI and sign up free (or sign in). You can apply from the job detail page; match scores and skill gaps appear when your profile is complete. DWS Group may attach structured assessments to interview rounds after you apply.
- Does Feedback AI show a match score for this AVP - Data Engineer | Bangalore, IN role?
- Yes after you add a resume or skills. Match score ranks this role against your profile — skills met, gaps, level, and location — so you prioritise applications where fit is strongest.
- Is AVP - Data Engineer | Bangalore, IN remote or on-site in Bengaluru, Karnataka?
- This listing is marked on_site with location Bengaluru, Karnataka. Confirm details on the job description before applying.
- What skills matter for this AVP - Data Engineer | Bangalore, IN role at DWS Group?
- This is a mid-level AVP - Data Engineer | Bangalore, IN role. Key skills include skills listed in the job description. Feedback AI highlights matched vs missing skills on your profile after signup.