Job Description Data Engineer

Experience: 4–8 Years
Role: Data Engineer

Role Overview

We are looking for an experienced Data Engineer with 4–8 years of experience in designing, developing, and maintaining scalable data pipelines and data platforms. The ideal candidate should have solid hands-on experience with SQL, Python, PySpark, cloud-based data engineering, ETL tools, data warehousing, and orchestration frameworks.

The candidate will be responsible for building reliable data pipelines, integrating data from multiple sources, implementing data transformation processes, and supporting scalable data solutions across cloud settings.

Key Responsibilities
Design, develop, and maintain scalable ETL/ELT data pipelines for processing structured and unstructured data.
Develop data transformation and processing solutions using Python, SQL, and PySpark.
Build and manage data pipelines using platforms such as Databricks, AWS Glue, and Snowflake.
Work with cloud platforms including AWS, Azure, and/or GCP to develop and deploy data engineering solutions.




Design and implement data warehouses, data marts, and data models to support analytical and reporting requirements.
Work with databases and cloud data platforms such as BigQuery, Amazon Redshift, and SQL Server.
Develop and manage data workflows and pipeline orchestration using Apache Airflow.
Work with streaming and real-time data processing using Apache Kafka.
Implement data quality, validation, monitoring, error handling, and performance optimization across data pipelines.
Collaborate with BI and analytics teams to support reporting and visualization requirements using Power BI, Tableau, and Looker.
Implement and maintain CI/CD practices for data pipelines, code, and deployments.
Troubleshoot pipeline failures, data issues, and performance bottlenecks and provide effective solutions.
Follow best practices related to data security, governance, scalability, reliability, and maintainability.

📌 Data Engineer Chennai (India)
🏢 fluid.live
📍 India