Databricks Engineer (Contract)

Posted Yesterday
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Calgary, AB, CAN
In-Office
Senior level
Artificial Intelligence • Business Intelligence • Consulting • Big Data Analytics
The Role
Designs, builds, migrates, and optimizes modern data platforms on Azure Databricks. Responsibilities include developing batch and streaming pipelines, implementing Delta Lake and Unity Catalog governance, integrating Azure services, improving performance and cost, supporting data migrations, and applying CI/CD, security, and data quality practices. The role involves architecture decisions, client collaboration, knowledge transfer, documentation, and hands-on delivery at client locations in Calgary.
Summary Generated by Built In

We are seeking an experienced Databricks Engineer to join our delivery team on a contract basis to design, build, and optimize modern data platforms on Azure Databricks. In this strategic role, you will work directly with both Data Elephant and client data and analytics teams, helping them migrate, modernize, and scale their data workloads while applying best practices in data engineering, security, ML, AI and data governance. This is a hands-on engineering role with strong exposure to architecture decisions, client interaction, and end-to-end delivery.


Responsibilities

  • Play an integral project team role in the implementation of modern data platforms and architectures on Databricks (including ETL, workload migrations, and Unity Catalog).
  • Design and implement data pipelines using Azure Databricks (PySpark, SQL)
  • Build and optimize batch and streaming data workloads
  • Migrate legacy data workloads to Azure + Databricks
  • Implement Delta Lake patterns (medallion architecture, CDC, data quality)
  • Integrate Databricks with Azure services such as ADLS, ADF, Azure Key Vault and DevOps/Github
  • Optimize performance and cost (cluster sizing, job orchestration, query tuning)
  • Collaborate with solution architects, analytics engineers, and client stakeholders
  • Contribute to reusable accelerators, standards, and internal best practices
  • Support client enablement through knowledge transfer and documentation
  • Provide hands-on solution delivery, including guiding and working closely with client engineers and ensuring best practices.
  • Implement governance models and Unity Catalog including data access, lineage, and security frameworks.

QUALIFICATIONS

  • 7+ years of experience in data engineering.
  • 4+ years of recent, hands-on experience building production solutions with Databricks, including advanced features such as Delta Lake, Unity Catalog, and MLflow.
  • Strong experience developing data pipelines using PySpark and SQL.
  • Proven experience leading large-scale data migrations, including ETL workloads and cloud platform migrations.
  • Strong expertise with Microsoft Azure and experience working with Azure data services, including ADLS, Azure Data Factory (ADF), Synapse Analytics, Azure Key Vault, and Azure DevOps.
  • Strong understanding of modern data architectures, including lakehouse, medallion architecture, and ELT/ETL.
  • Experience implementing CI/CD practices for data workloads.
  • Strong understanding of enterprise data governance, security, and compliance best practices.
  • Excellent communication skills with experience working directly with client teams.
  • Previous consulting or professional services experience is strongly preferred.
  • Databricks and Microsoft Azure certifications are considered an asset.

Be part of Canada’s leading boutique consulting firm focused on Databricks and modern data platforms.

  • Work on challenging, high-impact projects with mid-sized and enterprise clients across industries
  • Collaborate with a senior, high-performing team that values speed, pragmatism, and client success.

This role requires regular onsite work at a client location in Calgary. 

Skills Required

  • 7+ years of experience in data engineering
  • 4+ years of recent hands-on experience building production solutions with Databricks
  • Experience with Delta Lake, Unity Catalog, and MLflow
  • Strong experience developing data pipelines using PySpark and SQL
  • Experience leading large-scale data migrations, including ETL workloads and cloud platform migrations
  • Strong expertise with Microsoft Azure and Azure data services, including ADLS, Azure Data Factory, Synapse Analytics, Azure Key Vault, and Azure DevOps
  • Understanding of modern data architectures, including lakehouse, medallion architecture, and ELT/ETL
  • Experience implementing CI/CD practices for data workloads
  • Understanding of enterprise data governance, security, and compliance best practices
  • Excellent communication skills and experience working directly with client teams
  • Previous consulting or professional services experience
  • Databricks and Microsoft Azure certifications
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The Company
27 Employees
Year Founded: 2022

What We Do

Data Elephant is a Vancouver-based consultancy helping organizations modernize data infrastructure and platforms to improve decision-making, self-service reporting, advanced analytics, AI, and machine learning. Its full-stack services include data strategy, governance, architecture and engineering, business intelligence, advanced analytics, generative AI, and cloud foundations. The company partners with clients from strategy through execution, combining technical delivery and strategic guidance to address data challenges and create measurable business outcomes.

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