Job Title : Senior Data Architect & Engineering Lead

Location : New Delhi/Bangalore (Hybrid)

Experience : 7-10 years

Role Overview :

You will lead end-to-end data architecture across lakehouse/warehouse ecosystems and drive the engineering roadmapowning standards, governance, scalability, and cost efficiency. You will mentor teams, partner with product and platform leaders, and ensure data enables advanced analytics and AI initiatives.

Key Responsibilities :

- Architecture Ownership : Define and evolve domain-driven, event-driven, and lakehouse architectures (Delta/Apache Iceberg/Hudi).

- Platform Strategy : Select and implement platform components (streaming, storage, warehouse, orchestration, catalog, observability); guide buy-vs-build.

- Scalable Engineering : Lead the design of batch/streaming pipelines, CDC, change-data capture, and real-time serving layers.

- Data Governance : Establish data standards, access models, PII redaction, retention policies, and audit mechanisms; champion data contracts.

- Cost & Performance Optimization : Right-size compute/storage, implement workload management, caching, partitioning/clustering, Z-ordering.

- ML/AI Readiness : Enable feature stores, model-ready datasets, and MLOps integrations with reproducible data.

- Leadership & Mentoring : Coach engineers, run design reviews, and foster a culture of quality and automation.

- Stakeholder Management : Translate business strategy into data roadmaps; drive cross-functional programs and migrations.

- Risk & Security : Own compliance postureencryption, secrets management, key rotation, and incident playbooks.

- Documentation & Enablement : Build reference architectures, blueprints, reusable templates, and internal training.

Required Skills :

- Deep expertise in data modeling, distributed systems, warehouse/lakehouse (Snowflake/BigQuery/Redshift + Delta/Iceberg).

- Advanced SQL, Python/Scala, and Spark; strong command over stream processing (Kafka/Flink/Spark Structured Streaming).

- Proven experience with orchestration (Airflow/Prefect), dbt, CI/CD, IaC (Terraform), and containerization (Docker/Kubernetes).

- Robust understanding of security, governance, data privacy, lineage, cataloging, and observability.

- Architectural leadership : ADRs (Architecture Decision Records), RFCs, cost modeling, and vendor evaluation.

Preferred Qualifications :

- Experience with microservices data patterns, Data Mesh, event sourcing, and CQRS.

- Hands-on with feature stores (Feast/Tecton), ML pipelines (Kubeflow/Vertex/Azure ML), and MLOps practices.

- Exposure to genAI data considerations (vector stores, embeddings, retrieval pipelines).

- Prior leadership of multi-cloud or large migration programs.

- Azure/AWS certifications preferred

Notice period : 30 days