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Be | Shaping the Future Verified
Consulting, Financial Technology

Senior Data-Backend Engineer

RemoteRemoteContractSeniorPosted 1 month agoHidden Gem · Himalayas

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Required skills

  • API design
  • modular monolith architecture
  • CI/CD
  • containerization
  • production APIs
  • backend automation
  • Microsoft Azure
  • compute
  • networking
  • identity

Nice to have

  • developer platforms
  • internal tools
  • self-service portals
  • Terraform
  • Databricks
  • Power BI

Role summary

We are seeking a Senior Data-Backend Engineer for a full-remote contract role on the Analytics Workspaces Platform team. The mission is to accelerate the analytics engineering lifecycle by providing tooling, automation, and guardrails for Databricks and Power BI workspaces. Responsibilities include designing and building platform APIs, architecting a modular monolith backend, creating CI/CD pipelines for analytics artifacts, implementing automation workflows for cost and compliance, and instrumenting operational visibility. The role requires strong software engineering fundamentals, cloud architecture experience on Azure, and proficiency in Python.

Contract Type: B2B

Way of working: Full-Remote

We 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 boundaries

Preferred:- 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 scale

Originally posted on Himalayas

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