Position Title: Principal Data Engineer – Nexus Platform

Career Level: P4

Job Category: AVP

Role Type: Hybrid

Job Location: Bangalore

About the Team:

The data engineering team is community of dedicated professionals committed to designing, building, and maintaining data platform solutions for the organization.

Impact

We are seeking an experienced Principal Data Engineer to join our Enterprise Data & Analytics (ED&A) organization. This is a senior, hands-on role for a seasoned data professional (15+ years) who can lead technology experimentation, drive proof-of-concepts (PoCs), and confidently validate architectural decisions for a modern enterprise data platform.

You will operate at the intersection of architecture, innovation, and engineering, working closely with:

• Enterprise Data Architects

• Innovation & Advanced Analytics teams

• Data Modeling Centers of Excellence (CoEs)

This role is critical in accelerating the adoption of new technologies, validating architectural patterns, and converting ideas into scalable, production-ready solutions.

Key Deliverables

1. Lead PoCs & Technology Evaluation

Design and execute end-to-end PoCs across the modern data stack

Evaluate emerging tools and capabilities in areas such as:

Data ingestion and integration

Data modeling and transformation

Data observability and quality

AI/ML enablement on data platforms

Provide clear, assertive recommendations backed by:

Performance benchmarks

Scalability considerations

Cost analysis and trade-offs

Validate architectural patterns and guide adoption decisions

2. Nexus Platform Enablement (Hands-on Leadership)

Drive implementation and validation across the Nexus platform stack

Ingestion & Landing

Architect and prototype ingestion patterns using:

CDC tools (e.g., Qlik Replicate)

API-driven ingestion and event-based patterns

Define scalable and governed landing strategies using:

AWS S3 and Lake Formation

Core Data Platform (Snowflake | Data Vault 2.0)

Lead design and validation of:

Raw Vault (Hubs, Links, Satellites)

Business Vault transformations

Ensure adherence to enterprise Data Vault 2.0 standards

Optimize Snowflake workloads for performance and cost

Transformation & Data Contracts (DBT)

Establish and validate DBT-based transformation frameworks

Define best practices for:

Modular modeling

Data contracts and testing

Build reusable macros and frameworks

Orchestration (Astronomer / Airflow)

Define orchestration patterns and standards

Validate pipeline reliability, dependency management, and scalability

Real-Time & API Enablement

Prototype and validate event-driven data patterns

Drive API-based data access using microservices (Fargate/Lambda)

Enable near real-time and operational analytics use cases

3. Collaboration with CoEs & Innovation Teams

Work closely with Data Modeling CoEs to:

Ensure proper application of Data Vault 2.0

Enhance modeling standards and automation

Partner with Innovation teams to:

Experiment with new technologies

Accelerate advanced analytics capabilities

Act as a bridge between architecture vision and engineering execution

4. Data Quality, Governance & Observability

Embed data quality into pipelines using:

DBT testing frameworks

Snowflake-based validation logic

Collaborate with governance teams to integrate:

Collibra (metadata, lineage)

BigID (data classification and compliance)

Ensure all PoCs and solutions align with enterprise governance standards

5. Accelerators, Standards & Reusability

Develop reusable frameworks, templates, and accelerators

Contribute to:

Platform playbooks

Engineering standards

Architecture reference patterns

Enable faster onboarding and adoption of Nexus capabilities

Skills and Qualification

Functional Skills:

Assertive decision-maker – able to evaluate options and confidently recommend solutions

Highly hands-on – leads by building and prototyping

Innovation-driven – constantly explores and tests new approaches

Collaborative leader – works effectively across architects, CoEs, and engineering teams

Execution-oriented – converts ideas into working, scalable solutions

Mentor & influencer – elevates team capability through guidance and best practices

Technical/Business Skills:

• 15+ years of experience in data engineering, data platforms, or data architecture

• Deep hands-on expertise with:

• AWS (S3, Lambda, IAM, Lake Formation, Fargate)

• Snowflake (advanced SQL, performance tuning, data modeling)

• Strong experience with:

• Data Vault 2.0 methodology

• Modern data architectures (lakehouse, event-driven patterns)

• Proven track record of:

• Leading and delivering complex PoCs

• Making technology recommendations and architecture decisions

• Hands-on experience with:

• DBT (models, macros, testing)

• Airflow / Astronomer

• Strong programming skills in Python and SQL

Relationships & Collaboration

Reports to: Associate Director - Data Engineering

Partners: Senior leaders and cross-functional teams

Leads: A team of Data Engineering associates

Accessibility Needs

We are committed to providing an inclusive and accessible hiring process. If you require accommodations at any stage (e.g. application, interviews, onboarding) please let us know, and we will work with you to ensure a seamless experience.