Databricks & Data Engineer || Remote (Canada) || Fulltime FTE
Acestack
Databricks & Data Engineer
Job Type: Full-Time FTE
Location: Canada
Work Arrangement: Remote
Job Summary
We are seeking an experienced Databricks & Data Engineer with strong expertise in Databricks, Python, SQL, PySpark, and AWS to design, develop, and optimize scalable data platforms and ETL/ELT pipelines. The ideal candidate will have strong hands-on data engineering experience, technical leadership capabilities, and the ability to mentor engineering teams.
Required Qualifications
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7+ years of experience in Data Engineering .
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3+ years of hands-on experience with Databricks .
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Strong expertise in Python and SQL .
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Hands-on experience developing data applications and pipelines using PySpark .
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Strong experience with AWS cloud services .
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Experience designing and implementing ETL/ELT frameworks .
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Strong knowledge of Delta Lake, Spark optimization, and Databricks Runtime .
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Experience with data modeling, including dimensional and normalized data models .
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Experience with Git, CI/CD, and Agile methodologies .
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Strong communication, collaboration, and stakeholder management skills.
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Experience leading technical teams and mentoring data engineers.
Preferred Qualifications
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Experience migrating data platforms from Redshift, Snowflake, Teradata, Oracle, or Hadoop to Databricks.
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Experience with Unity Catalog and Databricks governance frameworks.
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Knowledge of data quality and data testing frameworks .
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Experience in Insurance, Banking, or Financial Services domains.
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AWS and/or Databricks certifications are preferred.
Key Responsibilities
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Design, develop, and maintain scalable data engineering solutions using Databricks, PySpark, Python, SQL, and AWS .
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Build and optimize robust ETL/ELT pipelines and data processing frameworks.
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Develop solutions using Delta Lake and Databricks Runtime while applying Spark performance optimization techniques.
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Support data platform modernization and migration initiatives.
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Implement data governance, quality, testing, and security best practices.
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Collaborate with business, data, and technology stakeholders to deliver high-quality data solutions.
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Provide technical leadership, code reviews, and mentoring to data engineering teams.
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Follow Agile development practices and CI/CD standards.
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