Power BI Developer+SSIS

What You Will Do

·          Design, develop, and maintain BI and data solutions using SQL Server technologies and Power BI

·          Write, debug, and optimize complex SQL queries to support reporting and analytics needs

·          Develop and support ETL processes using SQL Server Integration Services (SSIS)

·          Build and maintain semantic models using SQL Server Analysis Services (SSAS)

·          Create and enhance dashboards and reports using SQL Server Reporting Services (SSRS) and Power BI

·          Develop and maintain data design artifacts such as source‑to‑target mappings, data flow diagrams, and RCA documents

·          Partner with stakeholders to understand business requirements and translate them into scalable data solutions

·          Participate in Agile ceremonies and contribute to continuous improvement of data engineering practices

·          Ensure data quality, performance, and reliability across BI solutions

 

Who You Are (Basic Qualifications)

·          Bachelor’s degree in Computer Science, Engineering, or a related field or equivalent practical experience

·          At least 3 years of hands‑on experience in BI, data engineering, or analytics roles

·          Strong proficiency in SQL, including writing complex queries and performance optimization

·          Experience working with SSIS, SSAS, SSRS, and Power BI

·          Solid understanding of BI concepts, including OLTP vs. OLAP architectures

·          Experience working in an Agile development environment

·          Strong problem‑solving skills with the ability to work independently

·          Effective written and verbal communication skills

 

 

What Will Put You Ahead

·          Hands‑on experience with Python for data processing and analytics

·          Exposure to cloud and data platforms such as AWS (e.g., S3, Lambda, Glue, EC2, IAM) and/or Databricks (e.g., Spark, Delta Lake, notebooks, workflows)

·          Experience designing and deploying data solutions using Python and modern data frameworks

·          Experience executing AI or ML experiments that improved productivity or automation

·          Proven ability to deliver measurable business impact through AI‑driven or data‑driven solutions

·          Exposure to MLOps/LLMOps practices, including experiment tracking, model deployment, monitoring, and responsible AI considerations