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OSI Digital

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

  • Toronto, ON, Canada

Full-time

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Job details

Job type
Full-time
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Posting language
English
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Original job description

Job Title: Data Engineer / BI Developer – GCP, dbt & Power BI

Experience: 3–5 Years

Employment Type: Full-Time

Location: Toronto, 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

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Responsibilities

Design and maintain scalable data pipelines, BigQuery warehouse solutions, and reusable dbt transformations, while monitoring workflows and resolving pipeline and data-quality issues. Develop Power BI semantic models, reports, and dashboards; optimize SQL and BigQuery performance; and support validation, deployments, documentation, and production operations.

Requirements

Requires 2–4 years of experience in data engineering, business intelligence, or analytics engineering, with hands-on skills in BigQuery, Airflow, dbt, SQL, and Power BI. Candidates should understand data warehousing, ETL/ELT, dimensional modeling, data validation, and version control; experience with Snowflake, Databricks, Spark, Python, or other cloud platforms is an advantage.

Skills

  • Google BigQuery
  • Apache Airflow
  • dbt
  • SQL
  • Power BI
  • Data Engineering
  • Data Warehousing
  • ETL/ELT
  • Data Modeling
  • DAX
  • Power Query
  • Git
  • Python
  • Data Quality
  • Dashboard Development
  • Query Optimization

Visa sponsorship

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Categories

  • Data & Analytics
  • Technology
  • Software

Keywords

  • Google Cloud Platform
  • BigQuery
  • Apache Airflow
  • dbt Core
  • dbt Cloud
  • Power BI
  • SQL
  • Python
  • Git
  • Snowflake
  • Databricks
  • Apache Spark
  • Lakehouse Architecture
  • Cloud Storage
  • Cloud Composer
  • IAM
  • Dataflow
  • Pub/Sub
  • Azure
  • AWS
  • ETL/ELT
  • Data Warehousing
  • Dimensional Modeling
  • Star Schema
  • DAX
  • Power Query
  • Row-Level Security
  • Data Quality
  • CI/CD
  • Agile/Scrum

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