Platform Data Engineer

360insights; City of Moncton; On-site; CAD 90,000 - 120,000; Full time

Job summary

360insights is seeking a Data Platform Engineer to build and maintain our Microsoft Fabric data platform. This mid‑level role combines data engineering, BI development, and platform governance to deliver reliable analytics for internal and client reporting.

You will work across ingestion, modeling (bronze/silver/gold), CDC and Delta Lake workflows, and Power BI reporting, with AI-assisted tooling to improve efficiency and quality.

Qualifications

• Strong SQL skills with complex joins, window functions, and performance tuning.
• Proficiency in Python and PySpark or similar data frameworks.
• Experience with Power BI semantic modeling and DAX development.
• Experience with Git-based development workflows (branching, PRs, code reviews).
• Familiarity with AI-assisted development tools and workflows.

Responsibilities

• Build and maintain data transformation processes within Microsoft Fabric using PySpark notebooks and Dataflow Gen2.
• Develop and support bronze, silver, and gold data models following architecture standards.
• Implement incremental loads, CDC, data quality validations, watermarking, and Delta MERGE patterns.
• Monitor, diagnose, and improve data pipelines and platform reliability.
• Develop and maintain Power BI reports and semantic models; validate business outcomes.

Skills

SQL

Python

Power BI

Git workflows

AI tools

Cloud data platforms

Tools

Delta Lake

Databricks

Synapse

Snowflake

Power BI

Job description

About the role

The Data Platform Engineer is a hands‑on, mid-level role responsible for building, maintaining, and enhancing 360insights’ Microsoft Fabric data platform. Reporting to the Head of Data Platform, this position contributes to the delivery of reliable, scalable analytics solutions that support business reporting, operational insights, and client-facing reporting needs.

The role spans the full data lifecycle, including data ingestion, transformation, pipeline development, platform operations, documentation, Power BI development, and reporting modernization. Working within an AI-assisted engineering environment, the successful candidate will leverage modern development practices, automated workflows, and data platform technologies to improve reporting reliability, efficiency, and scalability.

This role is ideal for someone who enjoys combining technical problem-solving, data engineering, and business intelligence development while taking ownership of assigned data assets and contributing to platform evolution.

What you’ll do

Data Engineering & Lakehouse Development

• Build and maintain data transformation processes within Microsoft Fabric using PySpark notebooks and Dataflow Gen2.
• Develop and support bronze, silver, and gold data models following established architecture and modeling standards.
• Implement incremental loading strategies, data quality validations, change data capture (CDC), watermarking, and Delta MERGE patterns.
• Analyze and validate transformed data against legacy reporting sources and document findings.

Pipeline Operations & Platform Reliability

• Monitor and support data pipelines, lakehouses, semantic models, and platform processes.
• Investigate failures, identify root causes, and implement corrective and preventative solutions.
• Manage assigned workspace access, gateways, data connections, and related platform configurations.
• Monitor platform utilization, identify performance bottlenecks, and recommend improvements.
• Maintain platform monitoring and inventory solutions that track operational health and assets.

Reporting & Business Intelligence

• Develop and maintain Power BI semantic models, dashboards, and reports.
• Create and validate DAX measures using established standards and best practices.
• Partner with stakeholders to gather reporting requirements and validate business outcomes.
• Develop and support custom internal and client-facing reports using governed Fabric data.
• Assist with the migration of legacy SSIS and TeamCity reporting workflows to Microsoft Fabric.
• Build and maintain automated report generation and distribution processes.

Documentation & Governance

• Maintain accurate documentation for data structures, transformations, and business rules.
• Contribute updates through established documentation and review processes.
• Ensure schema references, wiki content, and platform documentation remain current and accurate.
• Support documentation audits and resolve gaps, inconsistencies, or outdated information.

Continuous Improvement & Collaboration

• Participate in design discussions and recommend platform enhancements.
• Follow established AI-assisted engineering and review workflows.
• Use AI-supported development tools to improve solution quality and productivity while validating outputs independently.
• Collaborate with data, reporting, and business stakeholders to support operational and strategic objectives.

What you’ll bring

• 2-5 years of experience in Data Engineering, Analytics Engineering, Business Intelligence, or a related discipline.
• Experience working with modern cloud data platforms such as Microsoft Fabric, Databricks, Synapse, or Snowflake.
• Experience building and supporting production data pipelines and data transformation processes.
• Experience using Git-based development workflows, including branching, pull requests, and code reviews.
• Experience working with AI-assisted development tools and willingness to adopt AI-enabled workflows.

Technical Skills

• Strong SQL skills, including:
• • Complex joins
  • Window functions
  • Query optimization and performance analysis
• Proficiency in Python and experience with PySpark or similar data transformation frameworks.
• Knowledge of data warehousing, data modeling, and ETL/ELT best practices.
• Experience implementing:
• • Incremental data loads
  • Data quality validation
  • Change Data Capture (CDC)
  • Delta Lake or similar technologies
• Power BI development experience, including:
• • Semantic modeling
  • DAX development
  • Report and dashboard creation

Professional Skills

• Strong analytical and problem-solving abilities.
• Ability to independently investigate issues and validate solutions using evidence and data.
• Strong attention to detail and commitment to documentation.
• Ability to balance independent ownership with appropriate escalation and collaboration.
• Effective communication and stakeholder management skills.
• Continuous learning mindset and adaptability to new technologies and ways of working.

Preferred Qualifications

• Microsoft DP-600 or DP-700 certification.
• Experience with Delta Lake and medallion architecture.
• Experience with SQL Server, MySQL, or Amazon Redshift.
• Familiarity with Markdown-based documentation or docs-as-code practices.
• Experience supporting incentive, rebate, or loyalty program data environments.
• Experience with Power BI Paginated Reports, SSIS, TeamCity, custom report generation, or automated report distribution workflows.

AI Fluency

• Comfortable using AI-supported development tools to improve productivity and quality.
• Able to guide AI tools effectively, review generated outputs critically, identify errors, and validate results independently.