Role Overview :

10+ years of hands-on experience in data engineering with a strong focus on ETL/ELT pipeline development.

Technical Requirements :

- Strong proficiency in SQL and at least one programming language (Python preferred).

- Hands-on experience with ETL/orchestration tools such as Apache Airflow, dbt, Informatica, Talend, or SSIS.

- Solid experience with cloud data platforms (AWS Redshift/Glue, Azure Data Factory/Synapse, or GCP BigQuery/Dataflow).

- Experience working with both relational databases (PostgreSQL, MySQL, SQL Server) and big data technologies (Spark, Hadoop, Hive).

- Strong understanding of data warehousing concepts, dimensional modeling, and data architecture principles.

- Working knowledge of Power BI - building data models, writing DAX, and designing dashboards/reports connected to enterprise data pipelines.

- Understanding of Power BI performance optimization (incremental refresh, aggregations, query folding, Import vs. DirectQuery trade-offs).

- Experience with data pipeline orchestration, scheduling, and monitoring frameworks.

- Familiarity with version control (Git) and CI/CD pipelines for data engineering workflows.

Key Responsibilities :

- Design, develop, and maintain robust, scalable ETL/ELT pipelines to ingest data from diverse sources (databases, APIs, flat files, streaming sources).

- Build and optimize data models (star/snowflake schemas) for data warehouses and data lakes, structured for efficient BI consumption.

- Own end-to-end pipeline orchestration, monitoring, and error handling to ensure high reliability and data quality.

- Optimize SQL queries and pipeline performance for large-scale datasets.

- Partner with BI developers and business stakeholders to design semantic layers and datasets that support Power BI dashboards and reports.

- Build and maintain Power BI data models (star schema), DAX measures, and dataset refresh pipelines, ensuring alignment with underlying ETL structures.

- Optimize Power BI datasets and queries for performance, including incremental refresh strategies and efficient data source connections (Import vs. DirectQuery).

- Implement data quality checks, validation frameworks, and observability/monitoring for pipelines.

- Manage and evolve CI/CD practices for data pipeline (and where applicable, Power BI deployment pipeline) releases.

- Ensure data governance, security, and row-level security (RLS) standards are met across pipelines and Power BI reports.

- Mentor junior data engineers and contribute to engineering best practices and documentation.

- Troubleshoot and resolve production pipeline and reporting issues, ensuring minimal downtime.

Logistics :

- Please send CV only if you can attend the interview on weekdays, with a short notice period (max 15 days only).

- Job Location : Chennai (Work From Office, working hours are 1:00 PM to 10:00 PM (IST), Monday to Friday).

- If this interests you kindly forward your latest updated profile as a reply to this mail & we will call you at your convenient time to provide more details.

- We would really appreciate it if you refer any of your friends and colleagues!