Data Engineer

Greetings of the day!

We have exciting permanent job opportunity with one of our client, a leading Data Analytics company.

Note: Please dont apply if your notice period is 60 or 90 days

Job Location: Bangalore,Chennai,Gurgaon

F2F interview location: Hyderabad on (19th sep 2026)Saturday

Role & responsibilities

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines to ingest, transform, and load data

from diverse sources

• Write and optimize advanced SQL queries for data extraction, transformation, validation, and reporting
• Build and maintain data models, warehouses, and semantic layers to support analytics, reporting, and

downstream consumption

• Work with cloud data platforms and services to enhance data processing, storage, and scalability
• Automate and orchestrate end-to-end data workflows using tools such as Airflow, dbt, Cloud

Composer, or Data Factory

• Collaborate with cross-functional stakeholders Data Architects, Data Scientists, Analysts, and

business teams to translate requirements into technical solutions

• Perform data validation, reconciliation, and quality checks to ensure accuracy, consistency, and

governance across pipelines

• Document data pipelines, schemas, and technical processes to support knowledge sharing and

maintainability

• Troubleshoot pipeline failures, performance bottlenecks, and data quality anomalies
• Mentor junior engineers and contribute to best practices, code reviews, and continuous improvement

(scope matched to seniority)

Skills & Experience

• 4-10 years of relevant experience in Data Engineering, Data Pipeline Development, or a related field
• Advanced SQL complex joins, CTEs, window functions, and query performance optimization
• Hands-on proficiency in Python and/or PySpark for data transformation, automation, and processing
• Proven experience building and maintaining ETL/ELT pipelines end-to-end
• Hands-on expertise in at least one cloud data platform (AWS, GCP, or Azure) and its associated

warehouse/lake service (Snowflake, BigQuery, Databricks, or Microsoft Fabric)

• Experience with workflow orchestration tools (Airflow, dbt, Cloud Composer, Data Factory, or similar)
• Strong problem-solving skills and the ability to collaborate effectively with technical and non-technical

stakeholders.