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Jobs / SuperBet / Senior Analytics Engineer - Tableau Cloud Platform
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Posted 2026-05-19

Senior Analytics Engineer - Tableau Cloud Platform

Description

We are looking for a Senior Analytics Engineer focusing on the Tableau ecosystem to help us scale and operate our Tableau Cloud platform and standardize how analytics content is governed, accessed, and supported across the company. This is an individual contributor engineering role focused on execution, quality, and operational ownership: building automation, implementing governance patterns, improving reliability, and creating the “paved paths” that make Tableau easy and safe to use at scale. You’ll partner closely with Platform/IT/Security, Data Engineering, and Analytics teams, and work alongside the Tableau platform lead to ship well-scoped platform outcomes end-to-end.

Responsibilities
  • Deliver medium-to-large, multi-step initiatives independently within the Tableau platform domain, taking ownership from problem definition through rollout and documentation
  • Support & explore Tableau Cloud+ ecosystem , including agentic AI features - Tableau Agent, Tableau Pulse and other venues of data exploration & insights within Tableau Cloud+ ecosystem
  • Explore other tools/platforms for data exploration and visualisation
  • Implement and evolve Tableau Cloud governance : project structure, permission boundaries, group-based access patterns, and guardrails to prevent long-term drift
  • Build automation and tooling around Tableau operational workflows (e.g., APIs/scripts) to reduce manual work, improve repeatability, and lower risk
  • Improve platform reliability and quality by identifying recurring operational issues (access friction, permission drift, content sprawl signals) and delivering concrete fixes
  • Write clear, practical documentation that enables self-serve for both content creators and content consumers (how-to guides, runbooks, standards & best practices)
  • Collaborate cross-functionally with Platform/IT/Security, analytics (platform) engineering, 3rd party consultancy stakeholders and others to coordinate changes that impact access, identity, and rollout sequencing
  • Raise the engineering bar in your area through thoughtful reviews, pragmatic testing/validation, and operational hygiene (measurable, repeatable, debuggable processes)
  • Collaborate with your core team colleagues from the Data Tooling team, ensuring holistic approach to the entire data architecture, with horizontal best practices supported and enforced
Requirements
  • Strong engineering and/or analytics background, proven experience building analytical datasets and metrics in a modern data warehouse (preferably Snowflake)
  • Proven delivery with Tableau , including understanding how data sources, extracts, and dashboard logic impact correctness, performance, and trust
  • Proven ability to deliver medium-to-large engineering work independently , by breaking down ambiguous requests into shippable milestones, communicating progress, and landing changes with high quality
  • Scripting/automation skills and comfort working with APIs and operational tooling
  • A production mindset: you care about reliability, maintainability, documentation, and operational ownership - not just shipping once but ensuring overall support and success
  • Working knowledge of access control concepts (roles/groups, inheritance, least privilege)
  • Strong collaboration and communication skills: you can coordinate with technical and non-technical stakeholders and write clear, actionable docs
  • Hands-on Tableau Server/Cloud administration experience (projects, permissions, site roles, extracts/schedules)
  • Familiarity with identity/provisioning concepts such as SSO/SAML and SCIM, and experience partnering with IT/security teams on access changes
  • Experience building platform runbooks and operational practices (rollouts, validation, troubleshooting playbooks)
  • Experience in data governance / catalog / lineage tooling (e.g., DataHub, Colibra, Informatica) and metadata continuity challenges
  • Experience operating BI platforms in high-growth environments where structure and definitions evolve quickly
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