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

Job summary

Design, develop, and maintain scalable data pipelines using Apache Airflow and Google BigQuery. Build reusable transformation models with dbt and create interactive dashboards using Power BI.

Job details

Job Title: Data Engineer / BI Developer – GCP, dbt & Power BI Experience: 3–5 Years Employment Type: Full-Time Location: Vancouver, BC Canada Job Summary We are looking for a Data Engineer / BI Developer with 2–4 years of experience in building cloud-based data pipelines, transformation frameworks, and analytical reporting solutions. The ideal candidate should have hands-on experience with Google BigQuery, Apache Airflow, dbt, SQL, and Power BI, along with a good understanding of data warehousing, ETL/ELT processes, data modeling, and dashboard development. Key Responsibilities Design, develop, and maintain scalable data pipelines using Apache Airflow. Develop and optimize data warehouse solutions using Google BigQuery. Build reusable and maintainable transformation models using dbt. Develop interactive reports and dashboards using Power BI. Write complex and optimized SQL queries for extraction, transformation, validation, and reporting. Create and maintain dimensional models, fact tables, views, and reporting datasets. Develop dbt models, tests, documentation, macros, and incremental processing logic. Monitor Airflow DAGs and troubleshoot pipeline and data-quality issues. Optimize BigQuery queries for performance and cost efficiency. Build Power BI semantic models, relationships, measures, calculated columns, and DAX calculations. Perform source-to-target validation and data reconciliation. Implement data-quality checks to ensure reliable and consistent reporting. Participate in code reviews, deployments, testing, and production support. Maintain technical documentation for pipelines, transformations, datasets, and dashboards. Required Skills 2–4 years of experience in Data Engineering, Business Intelligence, or Analytics Engineering. Strong hands-on experience with Google BigQuery. Hands-on experience developing and maintaining Apache Airflow DAGs. Good experience with dbt Core or dbt Cloud. Strong knowledge of SQL and query optimization. Hands-on experience with Power BI. Good understanding of: Power Query DAX Data modeling Power BI Service Dataset / semantic model refresh Row-Level Security (RLS) Understanding of ETL/ELT architecture and data warehousing concepts. Experience working with fact and dimension models and star-schema-based reporting solutions. Knowledge of data validation, reconciliation, and troubleshooting techniques. Experience using Git or similar version-control tools. Added Advantage / Good to Have Any hands-on experience with Snowflake will be an added advantage. Any experience with Databricks, Apache Spark, or Lakehouse architecture will be an added advantage. Experience with Python for data engineering or automation. Knowledge of additional GCP services such as: Cloud Storage Cloud Composer IAM Dataflow Pub/Sub Exposure to other cloud platforms such as Azure or AWS. Experience with CI/CD pipelines for dbt, Airflow, or Power BI deployments. Understanding of data governance, data quality, metadata management, and security concepts. Experience working in Agile/Scrum delivery environments. Preferred Candidate Profile The candidate should be capable of independently developing data pipelines and reporting solutions, troubleshooting technical issues, and working with business and technical stakeholders to translate requirements into scalable data solutions. Candidates with broader modern data-platform exposure, particularly Snowflake and Databricks, will be preferred. Primary Technology Stack: GCP | BigQuery | Airflow | dbt | SQL | Power BI | Git | Python Additional Advantage: Snowflake | Databricks | Spark | Azure | AWS

What you’ll do

Design, develop, and maintain scalable data pipelines using Apache Airflow and Google BigQuery. Build reusable transformation models with dbt and create interactive dashboards using Power BI.

Requirements

Requires 2–4 years of experience in Data Engineering or Business Intelligence with strong proficiency in SQL and cloud-based data platforms. Candidates should have hands-on experience with dbt, Airflow, and Power BI, along with a solid understanding of data warehousing concepts.

Listed skills

• Power BI · Preferred
• SQL · Preferred
• Git · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Google BigQuery
• Apache Airflow
• Dbt
• SQL
• Power BI
• Data Engineering
• Business Intelligence
• Data Modeling
• ETL/ELT
• Data Warehousing
• Python
• Git
• DAX
• Power Query
• Cloud Computing
• Data Quality
• Google Cloud Composer
• Technical Issues
• CI/CD
• Reporting Solutions
• Data Analysis Expressions (DAX)
• Git (Version Control System)
• Snowflake (Data Warehouse)
• Agile Methodology
• Amazon Web Services
• Automation
• Microsoft Azure
• Reconciliation
• Dashboard
• Version Control
• Code Review
• Directed Acyclic Graph (Directed Graphs)
• Data Validation
• Dataflow
• Data Governance
• Extract Transform Load (ETL)
• Excel Macros
• Scalability
• Python (Programming Language)
• Metadata Management
• Scrum (Software Development)
• Query Optimization
• Publish Subscribe
• SQL (Programming Language)
• Technical Documentation
• Troubleshooting (Problem Solving)
• Apache Spark
• Star Schema
• Databricks
• Data Pipelines

Job areas

• Data & Analytics
• Technology
• Software
• Engineering
• Power Business Intelligence Developer
• Business Intelligence Developer / Architect
• Software Developers

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