Senior Data Engineer – Databricks, Python, SQL & AWS

• Position: Senior Data Engineer – Databricks, Python, SQL & AWS
• Location: Toronto, ON (Remote)
• Employment Type: Full-Time

Job Summary:

We are seeking a Senior Data Engineer with 7+ years of experience and strong hands-on expertise in Databricks, PySpark, Python, SQL, and AWS. The candidate will design scalable data pipelines, optimize Spark workloads, implement ETL/ELT frameworks, and provide technical leadership.

Key Responsibilities:

• Design and develop scalable ETL/ELT pipelines using Databricks, PySpark, Python, and SQL.
• Build and optimize data solutions using Spark, Delta Lake, and Databricks Runtime.
• Develop cloud-based data solutions on AWS.
• Implement data modeling, data quality, testing, and governance practices.
• Optimize Spark jobs, SQL queries, clusters, and pipeline performance.
• Use Git, CI/CD, and Agile methodologies.
• Collaborate with stakeholders to translate business requirements into technical solutions.
• Lead technical initiatives and mentor data engineers.

Required Skills:

• 7+ years of Data Engineering experience.
• 3+ years of hands-on Databricks experience.
• Strong Python, SQL, and PySpark skills.
• Strong experience with AWS cloud services.
• Expertise in ETL/ELT, Delta Lake, Spark optimization, and Databricks Runtime.
• Knowledge of dimensional and normalized data modeling.
• Experience with Git, CI/CD, and Agile.
• Strong communication, stakeholder management, and leadership skills.

Preferred Qualifications:

• Experience migrating Redshift, Snowflake, Teradata, Oracle, or Hadoop platforms to Databricks.
• Experience with Unity Catalog and Databricks governance.
• Knowledge of data quality and automated testing frameworks.
• Experience in banking, insurance, or financial services.
• AWS and/or Databricks certifications preferred.