Job Title: Data Engineer – Databricks
Location: Onsite – Toronto, Canada
Employment Type: Contract
About the Role
We are seeking an experienced Data Engineer with a strong background in Databricks, Apache Spark, and modern cloud data platforms. The ideal candidate has over 5 years of experience designing, developing, and maintaining scalable data pipelines and lakehouse architectures in enterprise environments. You will work closely with solution architects, analysts, and cross-functional teams to build robust, high-performance data solutions supporting analytics and machine learning workloads.
Key Responsibilities
• Design and implement ETL/ELT pipelines using Databricks and Apache Spark for batch and streaming data.
• Develop and maintain Delta Lake architectures to unify structured and unstructured data.
• Implemented Medallion Architecture (Bronze/Silver/Gold) for structured, semi-structured, and streaming workloads.
• Collaborate with data architects, analysts, and data scientists to define and deliver scalable data solutions.
• Implement data governance, access control, and lineage using Unity Catalog, IAM, and encryption standards.
• Integrate Databricks with cloud services on AWS, Azure, or GCP (e.g., S3, ADLS, BigQuery, Glue, Data Factory, or Dataflow).
• Automate workflows using orchestration tools such as Airflow, dbt, or native cloud schedulers.
• Tune Databricks jobs and clusters for performance, scalability, and cost optimization.
• Apply DevOps principles for CI/CD automation in data engineering workflows.
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Required Qualifications
• 5+ years of professional experience in data engineering or data platform development.
• Hands-on experience with Databricks, Apache Spark, and Delta Lake.
• Experience with at least one major cloud platform — AWS, Azure, or GCP.
• Strong proficiency in Python or Scala for data processing and automation.
• Advanced knowledge of SQL, query performance tuning, and data modeling.
• Experience with data pipeline orchestration tools (Airflow, dbt, Step Functions, or equivalent).
• Understanding of data governance, security, and compliance best practices.
• Excellent communication skills and ability to work onsite in Toronto.
Preferred Skills
• Certifications in Databricks, AWS/Azure/GCP Data Engineering, or Apache Spark.
• Experience with Unity Catalog, MLflow, or data quality frameworks (e.g., Great Expectations).
• Familiarity with Terraform, Docker, or Git-based CI/CD pipelines.
• Prior experience in finance, legal tech, or enterprise data analytics environments.
• Strong analytical and problem-solving mindset with attention to detail.
