Senior ETL Data Engineer

Were 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. Youll 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. Youll 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

• 58 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