Deutsche Bank

Xtrackers SEA - Order C/R - AVP, Data Engineer

Deutsche Bank
Bengaluru/Bangalore
Not disclosed
Work from OfficeWork from Office
Full TimeFull Time
Min. 5 yearsMin. 5 years

Job Description

Xtrackers SEA - Order C/R - AVP, Data Engineer

Job Description:

Job Title: Xtrackers SEA - Order C/R - AVP, Data Engineer

Location: Bangalore, India

Role Description

We are seeking an experienced Data Engineer at AVP level to design, build, and optimize scalable data pipelines and data models on Snowflake. This role requires strong expertise in data modelling, ETL architecture, and multi-database environments (SQL Server, Oracle, PostgreSQL). The candidate will play a key role in defining data structures, ensuring data quality, and enabling reliable data consumption across systems, while leveraging AI tools to enhance productivity.

AI-Assisted Engineering (Primary Focus)

Actively leverage AI-powered tools (GitHub Copilot, Gemini, etc.) for:

  • Writing optimized SQL and transformation logic
  • Designing ETL pipelines and improving performance
  • Accelerating debugging, RCA, and documentation
  • Automating repetitive development and validation tasks
  • Ensure validation of AI-generated outputs for correctness, data integrity, and performance
  • Identify opportunities to use AI for improving data engineering workflows and productivity

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 optimize ETL pipelines using Snowflake for large-scale data processing
  • Build robust data ingestion frameworks from multiple upstream systems
  • Ensure high data quality, consistency, and availability across downstream consumers
  • Perform root cause analysis (RCA) for complex data and pipeline issues
  • Lead production support for critical data pipelines and ensure system stability
  • Collaborate with business teams to understand data requirements and translate them into scalable solutions
  • Work closely with architects and senior engineers to align data solutions with enterprise architecture
  • Design, develop, and optimize ETL pipelines using Snowflake for large-scale data processing
  • Build robust data ingestion frameworks from multiple upstream systems
  • Ensure high data quality, consistency, and availability across downstream consumers
  • Perform root cause analysis (RCA) for complex data and pipeline issues
  • Lead production support for critical data pipelines and ensure system stability
  • Collaborate with business teams to understand data requirements and translate them into scalable solutions
  • Work closely with architects and senior engineers to align data solutions with enterprise architecture

Data Modelling (Core Focus Area)

  • Design and implement dimensional data models (star schema, snowflake schema)
  • Work with fact and dimension tables for analytical and reporting use cases
  • Implement Slowly Changing Dimensions (SCD) for historical data tracking
  • Define data models for different layers (staging, curated, consumption)
  • Ensure data models are scalable, reusable, and aligned with business use cases
  • Optimize schema design for performance and efficient querying in Snowflake
  • Collaborate with stakeholders to evolve data models based on changing business requirements

Data Engineering and Processing

  • Design complex data transformations and large-scale batch processing pipelines
  • Handle incremental and full data loads efficiently
  • Optimize Snowflake usage (compute, storage, query performance)
  • Implement best practices for data partitioning, clustering, and efficient querying
  • Handle structured and semi-structured data where applicable

Data Quality and Governance

  • Define and implement data validation, reconciliation, and quality checks
  • Ensure data lineage, traceability, and auditability across pipelines
  • Identify and resolve data inconsistencies across systems
  • Follow enterprise data governance and compliance standards

Integration and Microservices

  • Integrate data pipelines with microservices and API-based systems
  • Enable data exposure for real-time and batch consumption
  • Collaborate with backend teams for data exchange patterns

Cloud and Platform Awareness

  • Work on Snowflake-based data platforms with good understanding of cloud concepts
  • Exposure to GCP services for data ingestion and orchestration (nice to have)
  • Ensure pipelines are scalable and cloud-native

Monitoring and Performance Optimization

  • Monitor ETL pipelines and data processes for failures and performance issues
  • Identify and fix performance bottlenecks in queries and transformations
  • Implement alerting and monitoring for proactive issue detection

SDLC, Release and Compliance

  • Drive deployment, validation, and release of data pipelines
  • Ensure compliance with SDLC processes and audit requirements
  • Document pipelines, data models, and transformation logic

Your skills and experience

  • Strong SQL expertise (advanced queries, performance tuning, optimization)
  • Hands-on experience with Snowflake for ETL and data modelling
  • Strong experience with relational databases (SQL Server, Oracle, PostgreSQL)
  • Solid understanding of data modelling concepts (star schema, SCD, dimensional modelling)
  • Experience working with ETL pipelines and data integration patterns
  • Exposure to microservices and API-based integration
  • Familiarity with version control (Git) and CI/CD processes
  • Awareness of cloud platforms (GCP preferred)

Problem Solving and Ownership

  • Strong analytical and problem-solving skills across data domains
  • Ability to handle complex data issues independently
  • Focus on long-term scalable solutions instead of quick fixes
  • Ownership of data pipelines and models end-to-end

Collaboration and Leadership

  • Mentor and guide junior data engineers
  • Collaborate with architects, developers, and business stakeholders
  • Drive best practices across data engineering and modelling
  • Act as a technical lead for data-related initiatives

Ways of Working

  • Strong communication skills across technical and business teams
  • Ability to work in Agile environments
  • Proactive approach toward improving data reliability and performance
  • Continuous learning mindset for new tools and technologies

What Makes This Role Unique

  • Strong focus on data modelling and Snowflake-based architecture
  • Opportunity to design scalable enterprise data models and pipelines
  • Exposure to AI-driven data engineering practices
  • Bridge between data engineering execution and data architecture design

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.

Experience Level

Executive Level

Job role

Work location
Work locationBangalore, Velankani Tech Park, India
Department
DepartmentData Science & Analytics
Role / Category
Role / CategoryDBA / Data warehousing
Employment type
Employment typeFull Time
Shift
ShiftDay Shift

Job requirements

Experience
ExperienceMin. 5 years

About company

Name
NameDeutsche Bank
Job posted by Deutsche Bank

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