Quantiphi

Databricks Engineer

Quantiphi$100K — $130K *
US-AnywhereRemote in Canada
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 7+ years experience in data engineering, preferably with Databricks
  • Bachelor's degree in Computer Science or related field
  • Hands-on experience with Databricks Workspaces, Clusters, and Jobs
  • Strong skills in PySpark, Spark SQL, and Scala
  • Expertise in building ETL/ELT pipelines and implementing Medallion Architecture
  • Experience with cloud platforms like AWS or Azure
  • Familiarity with AI-assisted development tools and responsible AI usage

Responsibilities

  • Design and build scalable data pipelines using Databricks and Apache Spark
  • Develop and maintain ETL/ELT workflows for large datasets
  • Implement data solutions following Medallion Architecture (Bronze, Silver, Gold)
  • Optimize Delta Lake tables with advanced features
  • Orchestrate and monitor Databricks Workflows and jobs
  • Collaborate with cross-functional teams to deliver data products
  • Apply software engineering best practices, including CI/CD and automated testing

Benefits

  • Opportunity to work at a rapidly growing AI-focused engineering firm
  • Collaborate with a talented team to tackle complex challenges
  • Engage with Fortune 500 companies in a research-oriented setting
  • Gain hands-on experience with advanced technologies and continual skill development
Full Job Description

Role:Databricks Data Engineer

Experience Level: 7+ years of experience

Employment type: Full time

Work location:Remote Canada

What you’ll do:

We are looking for an experienced Databricks Data Engineer to join our Insights & Analytics team on a contract basis. In this role, you will design, build, and optimize scalable data pipelines using the Databricks platform while leveraging modern software engineering practices. You'll work closely with cross-functional teams to deliver high-quality data solutions that support analytics, reporting, and AI-driven initiatives.

The ideal candidate has deep expertise in Databricks, Spark, and cloud-native data engineering, along with experience using AI-assisted development tools responsibly to improve engineering productivity and code quality.

Role & Responsibilities:

  • Design, develop, and maintain scalable data pipelines using Databricks and Apache Spark.

  • Build and optimize ETL/ELT workflows to ingest, transform, and curate large datasets.

  • Implement data solutions following Medallion Architecture (Bronze, Silver, Gold).

  • Develop high-performance PySpark and Spark SQL transformations.

  • Optimize Delta Lake tables using partitioning, optimization, vacuuming, and time travel capabilities.

  • Orchestrate and monitor Databricks Workflows and scheduled jobs.

  • Collaborate with analytics, engineering, and product teams to deliver reliable data products.

  • Apply software engineering best practices, including version control, automated testing, and CI/CD.

  • Utilize AI-assisted development tools for code generation, debugging, documentation, and productivity while validating outputs to ensure quality and accuracy.

  • Contribute to data quality, performance tuning, and operational excellence across the platform.

Essential Skills/Qualifications:

  • Bachelor's degree in Computer Science, Software Engineering, or a related field (or equivalent work experience)

  • Hands-on experience with Databricks Workspaces, Clusters, Jobs, and Unity Catalog

  • Strong knowledge of Delta Lake, including ACID transactions, Time Travel, OPTIMIZE, and VACUUM

  • Experience building and managing Databricks Workflows

  • Strong experience with PySpark, Spark SQL, and Scala

  • Expertise designing and building ETL/ELT pipelines

  • Experience implementing Medallion Architecture (Bronze/Silver/Gold)

  • Knowledge of incremental data loading patterns and pipeline optimization

  • Programming Languages: Python (Advanced) SQL (Advanced), Scala (Strong working knowledge)

  • Experience with at least one of the following cloud platform: AWS (Amazon S3, AWS Glue, Redshift), Azure (Azure Data Lake Storage Gen2 (ADLS Gen2),Azure Data Factory (ADF), Azure DevOps)

  • Experience using AI-powered developer tools for coding, debugging, testing, and documentation

  • Understanding of responsible AI usage, code validation, and quality assurance

  • DevOps & Engineering Practices: Git version control, CI/CD pipelines, Unit testing and automated validation for data transformations, Strong software engineering and code quality practices

Nice to have Skils:

  • Terraform or Databricks Asset Bundles

  • Experience building streaming data pipelines

  • dbt

  • Data quality and observability frameworks

  • MLflow

  • Java experience

  • Experience working in Agile/Scrum environments

What is in it for you:

  • Join one of the world’s fastest-growing AI-first digital engineering companies and make a real impact at scale.

  • Lead and collaborate with a high-energy team of talented, driven individuals solving complex, meaningful challenges.

  • Work with Fortune 500 companies and disruptive innovators in a research-driven environment with 60+ patents.

  • Stay ahead of the curve by gaining hands-on experience with cutting-edge AI, ML, data, and cloud technologies while continuously upskilling.

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!

About Quantiphi

Quantiphi is an artificial intelligence and machine learning services company that helps businesses transform their operations through the use of AI. The company provides a range of services, including data engineering, machine learning, computer vision, natural language processing, and predictive analytics. Quantiphi was founded in 2013 and is headquartered in King of Prussia, Pennsylvania.
Learn more about Quantiphi
Size
500 employees
Industry
Founded
2013

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