Consultant, Data Engineer(Databricks)

Project XToronto, ON
CA$86,000 - CA$125,000Hybrid

About The Position

We’re looking for a passionate and curious Data Engineer with strong DBT and Python skills and solid experience working with large-scale data solutions. You’ll play a key role in building high-quality, reusable ETL patterns and automating robust, scalable data pipelines that power analytics and business decision-making. Experience with Matillion ETL or Project X’s Data Pipeline Control (DPC) framework is a plus, and exposure to generative AI (GenAI) tools or techniques is considered an asset.

Requirements

  • 2+ years of hands-on experience in data engineering with a focus on Python-based development.
  • Proven experience using DBT (Data Build Tool) for data transformation and modeling
  • Experience with ETL development (Matillion, DPC, or other orchestration tools).
  • Strong SQL skills and ability to work with structured and semi-structured data.
  • Familiarity with cloud data platforms such as Snowflake, Azure, or AWS.
  • Understanding of data quality practices, error handling, and recovery strategies.
  • Ability to interpret mapping documents and accurately implement logic.
  • Experience with version control (e.g., Git) and CI/CD pipelines is a plus.
  • Bonus: Exposure to GenAI, LLMs, or machine learning workflows.

Nice To Haves

  • Experience in data modeling, data governance, or metadata frameworks.
  • Knowledge of data observability tools or building monitoring dashboards.
  • Familiarity with orchestration tools like Airflow or transformation tools like dbt.
  • Consulting experience or comfort working in fast-paced, client-facing environments.

Responsibilities

  • Develop, deploy, and maintain data pipelines using Python and tools such as Matillion ETL or DPC.
  • Collaborate with data architects and analysts to define and meet data integration requirements.
  • Translate mapping documents into production-ready data workflows.
  • Ensure data integrity by implementing quality checks, handling errors, and performing root cause analysis.
  • Apply tiered architecture design patterns (bronze/silver/gold models) to pipeline development.
  • Create or maintain metadata and control structures for visibility and traceability.
  • Work with cloud-based data warehouses (e.g., Snowflake, Azure Synapse, Redshift).
  • Participate in Agile processes, including sprint planning and reviews.
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