Senior Data Platform Engineer

Job not on LinkedIn

🔥 14 hours ago

🌐 Canada, United States – Remote

🇨🇦 Canada – Remote 🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 10%

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StoreForce

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2010

☁️ SaaS

🛒 Retail

🤝 B2B

💰 Private equity on 2023-04

SaaS • Retail • B2B

StoreForce is an all-in-one retail operations SaaS platform for specialty retailers that centralizes workforce management, KPI and performance management, retail execution, and employee engagement. It provides mobile and enterprise modules that give real-time visibility and enable retail executives, field managers, and store staff to communicate, execute strategies, optimize labor, and improve store performance.

📋 Description

• Build and run the lakehouse on Azure Databricks • Develop Spark and Delta Lake transformations, orchestration, and serving layers • Implement and maintain medallion and dimensional data models in Delta Lake • Tune Spark jobs, Photon, liquid clustering, storage, compute, and DBU spend • Maintain the governed Unity Catalog semantic layer and certified Metric Views • Enforce per-tenant row and column security at query time • Implement and reconcile StoreForce retail KPI logic • Onboard tenants and add KPIs through configuration and established patterns • Enforce data quality, data contracts, reconciliation, freshness, and volume checks • Maintain lineage and Lakehouse Monitoring and handle data incidents as production incidents • Deliver infrastructure and platform changes as code through CI/CD • Build and operate an LLM-powered analytics agent using Databricks AI tooling, Anthropic Claude, and OpenAI • Ensure tenant isolation, runtime guardrails, and automated evaluation quality gates • Work with the implementation partner during initial build and take ownership at handover • Serve as StoreForce’s go-to data engineer and support consuming teams • Maintain engineering standards and runbooks and triage data incidents

🎯 Requirements

• 5+ years building data pipelines or backend systems, including at least 2 years running a modern data stack in production • Hands-on production experience with Databricks: Unity Catalog, Delta Lake, Lakeflow Jobs and Spark Declarative Pipelines (or Workflows and Delta Live Tables), Databricks SQL, and Databricks Asset Bundles or equivalent as-code practice • Strong Apache Spark skills: PySpark, Spark SQL, Structured Streaming, query-plan analysis, shuffle and skew diagnosis, and job and compute tuning • Strong SQL, including window functions, complex joins, and query optimization • Strong Python for data work • Solid data modeling across medallion, dimensional, and incremental patterns • Experience tuning Delta tables, including liquid clustering, change data feed, OPTIMIZE, and VACUUM strategy • Experience implementing data quality and observability, including expectations, contracts, reconciliation, lineage, monitoring, and alerting • Hands-on experience with Anthropic Claude and OpenAI APIs for AI features • Fluent in modern software engineering practices, including version control, automated testing, and CI/CD • Databricks Certified Data Engineer Associate or Professional preferred • Experience with LLMs, multi-tenant SaaS data, SQL Server/Azure SQL Managed Instance CDC, Lakebase/PostgreSQL, embedded analytics, and platform handover preferred • Candidates must be based in the United States or Canada

🏖️ Benefits

• Flexible schedule • Employer-paid health benefits including dental, prescription drug coverage, and a Health Spending Account • RRSP Matching with First Time Home Buyer support • Company paid training and professional development • Extended Long Weekends and Religious Observance Days • Employee Referral Program • Spotlight Recognition Bonus Program • Dedicated Employee Assistance Program (EAP) • Accommodations available on request for candidates participating in all aspects of the selection process

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