The Business Data Engineer will design and maintain data pipelines, collaborate with business teams for analytics, and optimize data processing using Databricks and Power BI.
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).
#LI-MF1
Top Skills
Spark
APIs
Databricks
DevOps
Fivetran
Git
Jdbc
Odbc
Power BI
Python
Salesforce
Scala
SQL
Workday
Telesat Ottawa, Ontario, CAN Office
160 Elgin St, Suite 2100, , , Ottawa, Ontario , Canada, K2P 2P7
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