Job Description

We are looking for a hands-on Analytics Engineer who can work across both data engineering and analytics/reporting. This is not a Power BI-only role. The ideal candidate should be comfortable owning data tasks end-to-end — from understanding source data and building transformation pipelines to creating well-designed datasets and Power BI dashboards.

Key Responsibilities. • Build, maintain, and enhance data pipelines and transformation workflows using dbt and python DAG in Airflow. • Develop clean, reliable, and reusable data models for analytics and reporting. • Work with SQL and data warehouse platforms to investigate data, troubleshoot issues, and implement transformations. • Develop and maintain Power BI dashboards, reports, semantic models, and DAX measures. • Translate business requirements into appropriate data models and reporting solutions. • Perform data analysis, validation, reconciliation, and data quality checks. • Troubleshoot data issues across the pipeline, from source through transformation to reporting. • Take ownership of assigned tasks and independently drive them through development, testing, and completion. • Work closely with business, analytics, and engineering teams to deliver production-ready solutions. • AI Forward - Understand how to marry AI tools to enhance productivity on tasks Required Skills • Strong SQL and data analysis skills. • Strong Python for data pipelines for complex transformations and integrations. • Hands-on experience with dbt and/or modern ELT/data transformation practices. • Solid understanding of data modeling, including dimensional modeling, fact/dimension structures, and analytics datasets. • Experience working with a modern cloud data warehouse, preferably Snowflake. • Strong working experience with Power BI, including data modeling, DAX, dashboard development, and performance considerations