Senior ETL Data Engineer
Chennai, India
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingDesign, build and maintain ETL/ELT pipelines from databases, APIs, flat files and streams
Build star or snowflake data models for warehouses and lakes
Own pipeline orchestration, monitoring and error handling
Build and maintain Power BI data models, DAX measures and refresh pipelines
Optimize SQL queries and pipeline performance on large datasets
From the employer’s posting
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
Own end-to-end pipeline orchestration, monitoring, and error handling
Build and maintain Power BI data models (star schema), DAX measures, and dataset refresh pipelines
Optimize SQL queries and pipeline performance for large-scale datasets
Tools in this posting
- Python
- SQL
- AWS
- Azure
- BigQuery
- dbt
- GCP
- Hadoop
- Hive
- MySQL
- PostgreSQL
- Power BI
- Redshift
- Spark
- SQL Server
- Airflow
Source — Tool mentions in context
● 8-10 years of hands-on experience in data engineering with a strong focus on ETL/ELT pipeline development ● 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
● 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
● 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
● 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 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)
● 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
● 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)
● 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
● 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
● 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
● 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)
● 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
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 16, 2026 · 43 days ago
- Recorded sightings
- 24
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
Senior ETL Data Engineer
Experience: 8 - 10 years | Level: Senior
About the Role
We're looking for a Senior ETL Data Engineer
to design, build, and optimize scalable data pipelines that power analytics,
reporting, and machine learning initiatives across the organization. You'll own
the full lifecycle of data pipeline development — from ingestion to
transformation to delivery — while also enabling downstream BI consumption
through well-structured, reporting-ready datasets. You'll mentor junior
engineers and drive best practices in data engineering.
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
Required Skills & Qualifications
● 8-10 years of hands-on experience in data
engineering with a strong focus on ETL/ELT pipeline development
● 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
Source details
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Chennai, India
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