Data Engineer / BI Developer – GCP, dbt & Power BI

Role overview

Responsibilities

• Design, develop, and maintain scalable Apache Airflow data pipelines.
• Develop and optimize BigQuery warehouse solutions and queries for performance and cost efficiency.
• Build reusable dbt models, tests, documentation, macros, and incremental processing logic.
• Develop Power BI reports, dashboards, semantic models, relationships, measures, calculated columns, and DAX calculations.
• Write optimized SQL for extraction, transformation, validation, and reporting.
• Create and maintain dimensional models, fact tables, views, and reporting datasets.
• Monitor Airflow DAGs and troubleshoot pipeline and data-quality issues.
• Perform source-to-target validation and data reconciliation; implement data-quality checks.
• Participate in code reviews, deployments, testing, and production support.
• Maintain technical documentation for pipelines, transformations, datasets, and dashboards.

Required qualifications

• 2–4 years of experience in data engineering, business intelligence, or analytics engineering.
• Strong hands-on experience with Google BigQuery, Apache Airflow DAGs, dbt Core or dbt Cloud, SQL, and Power BI.
• Understanding of Power Query, DAX, Power BI Service, semantic-model refresh, and row-level security.
• Understanding of ETL/ELT architecture, data warehousing, fact and dimension models, and star-schema reporting.
• Knowledge of data validation, reconciliation, and troubleshooting techniques.
• Experience with Git or similar version-control tools.

Advantageous experience

• Snowflake, Databricks, Apache Spark, or Lakehouse architecture is advantageous.
• Python for data engineering or automation is advantageous.
• Additional GCP services, Azure or AWS, CI/CD pipelines, data governance, and Agile/Scrum experience are advantageous.

Candidate profile