Senior Power BI Engineer

Role overview

Lead a hands-on review and modernization of a business intelligence stack that supports finance and executive reporting. The work spans data ingestion, warehouse performance, and Power BI, with a focus on fresher, more reliable data, lower operating costs, and consistent self-service metrics. You will assess options, implement improvements, and transfer knowledge to the internal team.

Responsibilities

- Assess ingestion pipelines, warehouse structures, SQL queries, and existing reports to identify performance, reliability, and cost improvements. - Compare approaches for warehousing, change data capture, transformation, and reporting; run proofs of concept and recommend solutions based on cost, performance, effort, and migration risk. - Improve AWS Glue jobs and enable near-real-time replication from PostgreSQL to Amazon Redshift while limiting production impact. - Tune Redshift schemas, models, distribution and sort keys, workload management, and queries; build data marts for key business areas. - Rationalize reports and datasets, create a certified Power BI semantic model for shared business measures, and rebuild executive dashboards for flexible analysis. - Add pipeline monitoring, alerts, and data quality checks; document the architecture and operating practices, and support team knowledge transfer.

Requirements

- At least seven years in data or BI engineering, including two or more end-to-end BI stack assessments or rebuilds. - Extensive hands-on Redshift experience at scale, including modeling, workload management, query tuning, and cost optimization. - Knowledge of PostgreSQL replication internals, including logical replication, WAL, replication slots, and production workload impacts. - Production experience with AWS Glue and PySpark, plus at least one CDC approach such as AWS DMS, zero-ETL integration, or Debezium. - Strong Power BI skills across semantic models, DAX, star schemas, refresh modes, row-level security, and large reporting environments. - Strong SQL and Python; experience comparing data platforms and delivering measurable improvements to freshness, performance, cost, or reporting. - Clear communication and documentation skills, including explaining trade-offs to technical and non-technical audiences; able to overlap with US Pacific Time.

Nice to have

- Experience with dbt or similar transformation and testing frameworks, Terraform or comparable infrastructure-as-code, or data quality tools. - Relevant AWS or Microsoft data certifications, or experience with subscription metrics such as subscribers and churn.

Benefits and work setup

- Remote, hybrid, or office-based work with a flexible daytime schedule. - Annual leave, paid sick leave, private health insurance, work equipment, training access, and a sports-facility membership. - Regular performance reviews, with potential for promotion, bonuses, and pay increases.