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Senior Data-Backend Engineer

  • Be | Shaping the Future
  • Remote — United States
  • Contractor
  • Developer, Data Science

Contract Type: B2BWay of working: Full-RemoteWe are looking for a Data-Backend Engineer for Analytics Workspaces Platform.Mission:Accelerate the analytics engineering lifecycle and maximize engineers' deployment velocity, operational visibility, and financial control.We are a team own the analytics workspace components of the data platform: Databricks and Power BI. We provide the tooling, automation, and guardrails that let analytics engineers move fast without breaking things or blowing the budget. We build CI/CD pipelines for notebooks and reports, cost monitoring dashboards, workspace provisioning automation, and self-service templates that make the right thing the easy thing.We don't just administer workspaces. We treat them as a platform product, and we needs trong backend engineering to make that real.What you'll do: Design, build, and evolve the analytics workspace platform APIs: the programmatic interface through which analytics engineers provision, configure, discover, and govern their workspaces, clusters, and reports Architect and implement a modular monolith backend that orchestrates across Databricks APIs, Power BI REST APIs, and Azure infrastructure — resilient, observable, and easy to extend Build and maintain CI/CD pipelines for analytics artifacts — notebooks, dashboards, semantic models — so that promoting from dev to production is automated, testable, and auditable Design and implement automation workflows: cost attribution per team/project, budget alerts, auto-scaling policies, idle resource detection, and compliance guardrails Instrument and surface operational visibility: deployment metrics, run history trends, failure rates, and SLA adherence across all analytics workloads Own the workspace governance model as code: access control, environment separation, secret management, and data source connection policies enforced through automation, not manual stepsBuild self-service tooling and templates that reduce time-to-first-query and time-to-first dashboard for analytics engineers What we're looking forMust have:- Strong software engineering background: API design, modular monolith architecture, testing, CI/CD, and containerization- Proven experience building and maintaining production APIs and backend automation at scale- Deep cloud architecture experience on Microsoft Azure (compute, networking, identity, managed services, infrastructure-as-code)- Proficiency in Python (our primary automation languages)- Experience designing systems with clear bounded contexts, contract-driven APIs, and evolvable module boundariesPreferred:- Experience building developer platforms, internal tools, or self-service portals- Experience working with infrastructure-as-code such as Terraform- Familiarity with Databricks, Power BI, or comparable analytics platforms — not as a user, butunderstanding their API surfaces and operational models- Experience with FinOps practices — cost allocation, chargeback models, budget enforcement- Knowledge of event-driven architectures, workflow orchestration, or job scheduling at scaleOriginally posted on Himalayas