Databricks Lead – Python, PySpark, SQL & Supply Chain Analytics
- Toronto, ON, Canada
Full-time
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Job details
- Job type
- Full-time
- Apply by
- Experience
- Experience Required: 6-8 Years
- Posting language
- English
- Posted
Original job description
Databricks Lead – Python, PySpark, SQL & Supply Chain Analytics
Experience Required: 6-8 Years
Location: Toronto / Edmonton / Calgary
Work Model: Hybrid (3 days per week in office)
Role Summary
Seeking a Databricks Lead with strong expertise in Databricks to design, build, and operationalize scalable Supply Chain data products that deliver measurable business value. This role combines advanced analytics, data pipeline development, and product delivery to transform complex Supply Chain Management (SCM) data into trusted, governed, and actionable insights.
Key Responsibilities
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Develop analytics solutions that address Supply Chain business challenges, leveraging knowledge of oil & gas operations, procurement, supplier performance, spend analytics, and enterprise value drivers.
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Design, build, test, and optimize scalable ETL/ELT pipelines in Databricks using Python, PySpark, SQL, notebooks, jobs, and orchestration patterns to support reliable Silver and Gold data products.
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Transform and model data from ERP and enterprise platforms, including Oracle Cloud, SAP, ADW, Microsoft Dataflow, Dataverse, and other approved data sources.
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Build and evaluate machine learning, statistical, and AI-assisted solutions, including:
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Classification
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Forecasting
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Anomaly Detection
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Text Analytics
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Natural Language Processing (NLP)
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Utilize Databricks platform capabilities such as:
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Notebooks
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Jobs
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Workflows
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Unity Catalog
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SQL Warehouses
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Genie Code
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Lakeflow / Lakeflow Designer
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Maintain project documentation, including idea assessments, requirements, design documents, and weekly status reports.
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Communicate technical concepts, requirements, solution designs, and product details effectively to business stakeholders in clear, non-technical language.
Required Skills
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Databricks
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Python
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PySpark
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SQL / Oracle SQL
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Data Architecture & Data Modeling
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ETL / ELT Pipeline Development
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Machine Learning
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Supply Chain Analytics
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Data Integration and Data Transformation
Preferred Domain Experience
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Supply Chain Management (SCM)
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Oil & Gas Industry
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Procurement Analytics
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Supplier Performance Analytics
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Spend Analytics
More about this job
Responsibilities
Design, build, test, and optimize Databricks data pipelines and governed Silver and Gold data products using Python, PySpark, SQL, and enterprise data sources. Develop supply chain analytics and machine learning solutions, maintain project documentation, and communicate technical designs and product details to business stakeholders.
Requirements
The role requires 6–8 years of experience and expertise in Databricks, Python, PySpark, SQL, data architecture and modeling, ETL/ELT development, machine learning, and supply chain analytics. Experience with supply chain management, oil and gas, procurement, supplier performance, or spend analytics is preferred.
Skills
- Databricks
- Python
- PySpark
- SQL
- Oracle SQL
- Data Architecture
- Data Modeling
- ETL/ELT Pipeline Development
- Machine Learning
- Supply Chain Analytics
- Data Integration
- Data Transformation
- Forecasting
- Anomaly Detection
- Natural Language Processing
- Stakeholder Communication
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Logistics
- Energy
Keywords
- Databricks
- Python
- PySpark
- SQL
- Oracle SQL
- Data Architecture
- Data Modeling
- ETL
- ELT
- Machine Learning
- Supply Chain Management
- Oil and Gas
- Procurement Analytics
- Supplier Performance Analytics
- Spend Analytics
- Classification
- Forecasting
- Anomaly Detection
- Text Analytics
- Natural Language Processing
- Oracle Cloud
- SAP
- ADW
- Microsoft Dataflow
- Dataverse
- Unity Catalog
- SQL Warehouses
- Lakeflow
- Workflows
- Data Products