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