4Bell Technology

Staffing & Recruiting

Data Engineer II(R-1427)

1,500,000.00-2,000,000.00/A

Any Graduation

IT (Information Technology)

Full-time

Bangalore/Bengaluru

13-May-2026

Data Engineer SQL ETL Data warehousing and modeling Kubernetes Docker. Scala and Apache Spark Any cloud AWS/AZURE/GCP Lakehouse table formats

Job Description

Key Responsibilities

Data Pipeline Development & Optimization

● Build Scalable Pipelines: Design, develop, and maintain robust ETL/ELT pipelines using Scala and Apache Spark/Flink (Core, SQL, Streaming) to process massive datasets with low latency.

● Performance Tuning: optimize Spark jobs and SQL queries for efficiency, resource utilization, and speed.

● Lakehouse Implementation: Implement and manage data tables using modern Lakehouse formats like Apache Iceberg, Hudi, or Delta Lake, ensuring efficient storage and retrieval.

Data Management & Quality

● Data Modeling: Apply Medallion Architecture principles (Bronze/Silver/Gold) to structure data effectively for downstream analytics and ML use cases.

● Data Quality: Implement data validation checks and automated testing using frameworks (e.g., Deequ, Great Expectations) to ensure data accuracy and reliability.

● Observability: Integrate pipelines with observability tools to monitor data health, freshness, and lineage.

Cloud Native Engineering

● Cloud Infrastructure: Deploy and manage workloads on GCP DataProc and Kubernetes (K8s), leveraging containerization for scalable processing.

● Infrastructure as Code: Contribute to infrastructure automation and deployment scripts.

Collaboration & Innovation

● GenAI Integration: Explore and implement GenAI and Agentic workflows to automate data discovery and optimize engineering processes.

● Agile Delivery: Work closely with architects and product teams in an Agile/Scrum environment to deliver features iteratively.

● Code Reviews: Participate in code reviews to maintain code quality, standards, and best practices.

Required Skills:

● Experience: 3-5 years of hands-on experience in Data Engineering.

● Primary Tech Stack:

○ Strong proficiency in Scala and Apache Spark (Batch & Streaming).

○ Solid understanding of SQL and distributed computing concepts.

○ Experience with GCP (DataProc, GCS, BigQuery) or equivalent cloud platforms (AWS/Azure).

○ Hands-on experience with Kubernetes and Docker.

● Architecture & Storage:

○ Experience with Lakehouse table formats (Iceberg, Hudi, or Delta).

○ Understanding of data warehousing and modeling concepts (Star schema, Snowflake schema).

● Soft Skills:

○ Strong problem-solving skills and ability to work independently.

○ Good communication skills to collaborate with cross-functional teams.