Data & AI Platform Engineer

Job Responsibilities

• Support day-to-day operations for cloud data platforms, including workspace/project setup, access requests, basic configuration, and troubleshooting.
• Assist with platform hygiene by organizing environments, documenting standards, and improving repeatability.
• Help implement and maintain guardrails such as naming/tagging conventions, access patterns, and basic cost awareness.
• Contribute to CI/CD workflows for data and analytics assets—pipelines, jobs, semantic models, and reports—under mentorship.
• Help maintain reusable templates and checklists for deployments, covering approvals, promotion steps, rollback notes, and release documentation.
• Assist teams with onboarding and “how-to” enablement across core platforms (Fabric, Snowflake, or Databricks) and BI tools (Power
  
  BI or Tableau).
• Support basic performance triage for query/job failures, refresh issues, and workspace capacity constraints, escalating when necessary.
• Help build and maintain runbooks, including standard operating procedures, known issues, quick fixes, and escalation paths.
• Participate in incident response support—triage, notes, follow‑ups—and contribute to preventative improvements.
• Follow and reinforce least‑privilege access practices and secure secret handling (e.g., Azure Key Vault or secret scopes).
• Assist with data governance basics, such as PII handling expectations, row‑level access concepts, and environment separation.

• Minimum 2years of experience in data engineering, platform engineering, analytics engineering, or cloud operations (internships/co‑ops count).
• Comfortable with one or more of the following areas (not all): a cloud data platform (Snowflake—preferred—or Microsoft Fabric or Databricks); a BI platform (Power
  
  BI or Tableau); CI/CD concepts (Git, branching/PRs, basic pipelines); basic scripting in Python or Power Shell (or willingness to learn).
• Strong troubleshooting mindset—able to break problems down, gather evidence, and communicate clearly.
• Ability to document learnings, including runbooks, checklists, and short “how-to” guides.
• Exposure to cloud concepts such as identity/access, resource organization, and logging/monitoring.
• Familiarity with SQL and performance fundamentals (indexes/partitioning concepts, query plans at a high level).
• Understanding of data governance concepts, including PII, RLS/CLS, and environment separation.
• Any relevant certifications (Azure Fundamentals, Snowflake, Databricks, etc.).
• Demonstrated experience with AI/ML/GenAI enablement (model lifecycle, AI Search, Azure OpenAI integration, or MLOps).

For Colorado residents: $102,600‑$120,700. For Washington, Illinois, New York, and Southern California residents: $112,900‑$132,800. For Northern California residents: $118,000‑$138,800. Compensation may vary based on skills, role, and location.

• Medical, dental, and vision coverage.
• Generous PTO and paid sick time.
• Flexible work arrangements.
• 401(k) with profit sharing.
• Wellness program.
• Generous parental leave.
• 11 paid holidays.

Armanino provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics. In addition to federal law requirements, Armanino complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

A link to the consumer notice for job applicants can be found at