Business Data Engineer

We are seeking a motivated Business Data Engineer with 2–5 years of experience in Lakehouse environments. This hybrid role combines the technical rigor of a Data Engineer with the business insight of a Data Analyst, building reliable data pipelines while partnering with stakeholders to deliver impactful analytics and reporting.

The ideal candidate has hands-on experience with Databricks, PowerBI, advanced SQL, Fivetran, data integration from on-prem and cloud systems (including Workday and Salesforce), and solid understanding of Python and Databricks Notebooks.

Key Responsibilities:
• Design, develop, and maintain data pipelines and workflows for ingestion, transformation, and delivery of clean, reliable business data for analysis and reporting.
• Collaborate with business teams to gather requirements, perform data validation, and support UAT/demos.
• Extract, integrate, and transform data from diverse systems including Workday, Salesforce, on-prem and SaaS applications using APIs, JDBC/ODBC, and native/direct connections.
• Write and optimize advanced SQL for data modeling, transformation, and cost-efficient query execution.
• Build and optimize Power BI datasets, models, and dashboards for business insights and performance tracking.
• Use Databricks Notebooks with Python and/or Scala for data preparation, automation, and analysis.
• Monitor and optimize compute resources and job performance for cost control and efficiency.
• Document data pipelines, transformation logic, and architecture for transparency and maintainability.

Education and Experience:
• 2–5 years in a Data Engineering or Business Data Analysis role.
• Strong hands-on experience with Databricks (including Delta Lake, Spark SQL, and Notebooks).
• Strong working knowledge of Power BI (data modeling, DAX, dashboard design, publishing).
• Advanced SQL skills for large-scale data transformation and optimization.
• Proficiency in Python and/or Scala for data processing in Databricks.
• Proven experience with Fivetran or similar ETL/ELT tools for automated data ingestion.
• Experience integrating data from Business Applications like Workday and Salesforce (via APIs, reports, or connectors).
• Ability to manage and transform data from on-premises and cloud systems.
• Strong communication skills with experience in business requirement gathering and data storytelling.
• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Statistics, or a related field.
• Relevant certifications (e.g., Databricks Certified Data Engineer, Microsoft Power BI Data Analyst, Workday Reporting Specialist) are a plus.

Preferred / Nice-to-Have:
• Fundamental knowledge of Apache Spark (architecture, RDDs, DataFrames, optimization).
• Experience in query and compute cost optimization within Databricks or similar platforms.
• Familiarity with data governance, security, and metadata management.
• Exposure to CI/CD for data pipelines using Git or DevOps tools.
• GenAI Agents and/or ML experience

Decision Making and Supervision:
• Work under minimal supervision.
• Make decisions and recommendations requiring analysis and interpretation within established procedures.

Working Conditions:
• Generally comfortable working conditions with lifting and onsite installations.
• Moderate visual concentration in use of video display terminal.

The successful candidate must be able to work in Canada and obtain clearance under the Canadian Controlled Goods program (CGP).

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