{"id":3959577,"url":"https://alion.io/job/360insights-platform-data-engineer","title":"Platform Data Engineer","company":{"id":1922262,"name":"360insights","domain":"360insights.com","url":"https://alion.io/company/360insights","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Rippling","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Whitby, Canada"],"countries":["CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"Microsoft Fabric","optional":false},{"name":"Power BI","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"SSIS","optional":false},{"name":"TeamCity","optional":false},{"name":"Amazon Redshift","optional":true},{"name":"MySQL","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-21T21:33:24Z","employer_posted_date":"2026-10-21","last_verified_at":"2026-11-09T20:56:34Z","board_verified":true,"closed_at":null,"days_open":19,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":19},"description":"About 360insights\n360insights orchestrates how brands engage and grow their complex partner ecosystems. Our unified platform brings together streamlined experiences, incentives, and services so brands can coordinate go-to-market efforts with clarity, consistency, and control. Built for organizations with indirect channels and complex global incentive programs, we are trusted by leading brands worldwide.\nWe believe in “Experiences that create growth. Growth that creates experiences.” Through learning and development programs and mentorship, we provide the support, tools, and opportunities you need to grow and succeed as an Insighter.\nWe welcome talent from all backgrounds and are committed to equal opportunity regardless of race, religion, ethnicity, age, disability, sexual orientation, or gender identity. Accommodations are available throughout the hiring process upon request. Learn more about our DEIB vision on our website.\nAbout the role\nThe 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.\nThe 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.\nThis 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.\nWhat you'll do\nData Engineering & Lakehouse Development\nBuild and maintain data transformation processes within Microsoft Fabric using PySpark notebooks and Dataflow Gen2.\nDevelop and support bronze, silver, and gold data models following established architecture and modeling standards.\nImplement incremental loading strategies, data quality validations, change data capture (CDC), watermarking, and Delta MERGE patterns.\nAnalyze and validate transformed data against legacy reporting sources and document findings.\nPipeline Operations & Platform Reliability\nMonitor and support data pipelines, lakehouses, semantic models, and platform processes.\nInvestigate failures, identify root causes, and implement corrective and preventative solutions.\nManage assigned workspace access, gateways, data connections, and related platform configurations.\nMonitor platform utilization, identify performance bottlenecks, and recommend improvements.\nMaintain platform monitoring and inventory solutions that track operational health and assets.\nReporting & Business Intelligence\nDevelop and maintain Power BI semantic models, dashboards, and reports.\nCreate and validate DAX measures using established standards and best practices.\nPartner with stakeholders to gather reporting requirements and validate business outcomes.\nDevelop and support custom internal and client-facing reports using governed Fabric data.\nAssist with the migration of legacy SSIS and TeamCity reporting workflows to Microsoft Fabric.\nBuild and maintain automated report generation and distribution processes.\nDocumentation & Governance\nMaintain accurate documentation for data structures, transformations, and business rules.\nContribute updates through established documentation and review processes.\nEnsure schema references, wiki content, and platform documentation remain current and accurate.\nSupport documentation audits and resolve gaps, inconsistencies, or outdated information.\nContinuous Improvement & Collaboration\nParticipate in design discussions and recommend platform enhancements.\nFollow established AI-assisted engineering and review workflows.\nUse AI-supported development tools to improve solution quality and productivity while validating outputs independently.\nCollaborate with data, reporting, and business stakeholders to support operational and strategic objectives.\nWhat you'll bring\n2-5 years of experience in Data Engineering, Analytics Engineering, Business Intelligence, or a related discipline.\nExperience working with modern cloud data platforms such as Microsoft Fabric, Databricks, Synapse, or Snowflake.\nExperience building and supporting production data pipelines and data transformation processes.\nExperience using Git-based development workflows, including branching, pull requests, and code reviews.\nExperience working with AI-assisted development tools and willingness to adopt AI-enabled workflows.\nTechnical Skills\nStrong SQL skills, including:\nComplex joins\nWindow functions\nQuery optimization and performance analysis\n\nProficiency in Python and experience with PySpark or similar data transformation frameworks.\nKnowledge of data warehousing, data modeling, and ETL/ELT best practices.\nExperience implementing:\nIncremental data loads\nData quality validation\nChange Data Capture (CDC)\nDelta Lake or similar technologies\n\nPower BI development experience, including:\nSemantic modeling\nDAX development\nReport and dashboard creation\n\nProfessional Skills\nStrong analytical and problem-solving abilities.\nAbility to independently investigate issues and validate solutions using evidence and data.\nStrong attention to detail and commitment to documentation.\nAbility to balance independent ownership with appropriate escalation and collaboration.\nEffective communication and stakeholder management skills.\nContinuous learning mindset and adaptability to new technologies and ways of working.\nPreferred Qualifications\nMicrosoft DP-600 or DP-700 certification.\nExperience with Delta Lake and medallion architecture.\nExperience with SQL Server, MySQL, or Amazon Redshift.\nFamiliarity with Markdown-based documentation or docs-as-code practices.\nExperience supporting incentive, rebate, or loyalty program data environments.\nExperience with Power BI Paginated Reports, SSIS, TeamCity, custom report generation, or automated report distribution workflows.\nAI Fluency\nComfortable using AI-supported development tools to improve productivity and quality.\nAble to guide 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