Databricks Engineer

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Data Elephant

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2022

🤝 B2B

🏢 Enterprise

🤖 Artificial Intelligence

B2B • Enterprise • Artificial Intelligence

Data Elephant is a Vancouver-based data and analytics consultancy founded in 2022 that helps organizations modernize data infrastructure and platforms to enable self-service reporting, advanced analytics, AI, and machine learning. They offer end-to-end services including data strategy, cloud migration, data engineering (warehouses, lakes, lakehouses), governance, BI, MLOps, and GenAI proof-of-concept and training, partnering with cloud and analytics providers like AWS, Databricks, and Microsoft. Data Elephant serves enterprise clients across industries (energy, mining, finance, transportation, retail, sports, public sector) and positions itself as a trusted advisor delivering measurable business outcomes through collaboration and long-term partnerships.

📋 Description

• Lead 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 • Evaluate and prioritize high-value AI and ML use cases, embedding Generative AI into client strategies • Act as a thought leader by contributing to client workshops, executive roundtables, and industry discussions

🎯 Requirements

• 5–7+ years of experience in data engineering • 3+ years of hands-on experience with Databricks, including advanced features (Delta Lake, Unity Catalog, MLflow) • Proven experience leading large-scale data migrations (ETL, workloads, cloud platforms) • Strong expertise in Azure environments • Multi-cloud experience is an asset • Experience working with Azure data services (ADLS, ADF, Synapse, etc.) • Solid understanding of modern data architectures (lakehouse, medallion, ELT/ETL) • Experience with CI/CD for data workloads • Strong communication skills and comfort working directly with clients • Excellent understanding of data governance, security, and compliance in enterprise environments • Consulting experience is strongly preferred

🏖️ Benefits

• 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 • Databricks or cloud certifications required