Data Engineer, Data Innovation

MNP•Calgary, AB

3h•Onsite

About The Position

Inspirational, innovative and entrepreneurial - this is how we describe our empowered teams. Combine your passion with purpose and join a culture that is thriving in the face of change. Make an impact with our Technology - Development team as a Data Engineer. This diverse team of tech-savvy builders and problem solvers embraces digital transformation, and the possibilities technology brings to the future of our industry. We’re looking for team members who have a strong sense of ownership and drive, and who thrive on delivering high-quality solutions that are redefining the way MNP does business. MNP is proudly Canadian. Providing business strategies and solutions, we are a leading national accounting, tax and business advisory firm in Canada. Entrepreneurial to our core, our talented team members transcend obstacles into opportunities and are successfully transforming mid-market business practices.

Requirements

2 - 5 years of experience in Data Engineering, Analytics Engineering, or related roles
Bachelor’s degree in computer science, Engineering, or a related field
Experience with Azure Databricks (Apache Spark, Delta Lake)
Strong SQL skills and working knowledge of Python (PySpark preferred)
Understanding of ETL/ELT patterns and data pipeline design
Familiarity with Lakehouse architecture and data modeling concepts
Ability to work collaboratively in a fast-paced, innovation-focused team
Effective communication skills with both technical and non-technical stakeholders
Experience working with APIs and ingesting external data sources
Basic understanding of DevOps practices (CI/CD, Git, version control)

Nice To Haves

Exposure to Microsoft Fabric (OneLake, Lakehouse, Warehouse, Data Factory)
Exposure to hybrid data architectures (cloud + on-prem systems)
Experience with Spark Declaratives Pipelines and streaming or near real-time data pipelines
Experience with Power BI or Fabric reporting workloads
Awareness of data governance, security, and data quality best practices
Familiarity with AI/ML or LLM workflows

Responsibilities

Collaborate with data engineers, data scientists, BI developers, and business stakeholders to deliver modern data solutions
Design, build, and maintain data pipelines using Databricks (Delta Lake / Lakehouse) and Microsoft Fabric capabilities
Support development of a hybrid data platform architecture, integrating cloud (Azure / Fabric) and on-premises or legacy systems
Implement data ingestion and transformation workflows using Databricks Workflows / Jobs, Spark Declarative Pipelines, and Microsoft Fabric Data Factory / ADF
Contribute to the evolution of our Lakehouse architecture, including Medallion (Bronze/Silver/Gold) patterns
Work with structured and semi-structured data (CSV, JSON, Parquet, APIs)
Assist in implementing data governance and access controls using Unity Catalog and Microsoft Purview / Fabric governance features
Support CI/CD practices and deployment using Azure DevOps or Git-based workflows
Monitor and improve pipeline performance, reliability, and cost efficiency
Participate in experimentation with emerging capabilities such as AI/ML workflows, LLM integrations, and real-time data processing