Data Engineer - ETL/Azure Databricks

Job Title Data Engineer

Location Bangalore (Hybrid)

Interview Mode - Video

Duration : 6 Months Contract to hire/Full Time

Core Responsibilities :

- Data Architecture & Strategy

- Define enterprise-wide data models, standards, and integration patterns.

- Build data platforms on cloud/on-prem (Azure, AWS, GCP, Databricks, Snowflake, etc.).

- Establish guidelines for scalability, security, and cost optimization.

- Data Pipeline & Integration

- Design high-performance ETL/ELT pipelines.

- Implement real-time streaming (Kafka, Kinesis, Pub/Sub) and batch processing.

- Enable interoperability across operational, analytical, and AI systems.

- Governance & Quality

- Ensure compliance with data regulations (GDPR, HIPAA, SAMA, etc.).

- Build frameworks for metadata management, lineage, and observability.

- Work closely with Data Quality Management and Master Data Management (MDM).

- Collaboration

- Partner with business stakeholders to translate use cases into technical designs.

- Guide data engineers, analysts, and scientists on best practices.

- Align with enterprise architects and solution architects.

- Innovation & Future-Readiness

- Evaluate new technologies (e.g., lakehouse, vector databases, RAG).

- Architect solutions for AI/ML enablement.

- Drive automation and adoption of agentic AI in data workflows.

Typical Skill Set :

- Tech Foundations: SQL, Python/Scala/Java, distributed systems.

- Cloud & Data Platforms: Azure Synapse, AWS Redshift, GCP BigQuery, Snowflake, Databricks, Hadoop/Spark.

- Data Modeling: OLTP, OLAP, dimensional modeling, Data Vault, Knowledge Graphs.

- Integration Tools: Informatica, Talend, dbt, Airflow, Kafka.

- Architecture Practices: TOGAF, microservices, event-driven design.

- Soft Skills: Stakeholder management, solutioning, and leadership