About the role
We are seeking an experienced Senior Data Architect to own the foundations every other data-platform role depends on: Infrastructure-as-Code (Terraform), CI / CD for data and ML, FinOps, the Change Advisory Board, and the reference architecture. The board-level outcome is double-digit cloud cost reduction with credible attribution, alongside the platform principle that 'no production change happens outside the pipeline'.
Key Responsibilities:
- Adopt Terraform as the infrastructure standard for 100% of new and existing data-platform infrastructure; run weekly drift detection; design a reusable, versioned, documented module library.
- Build the governed CI / CD spine — every code change validated against pipeline-standard compliance, approval, and auto Jira update; target sub-hour deployment lead time and 100% coverage of core repos.
- Design and test rollback orchestration with sub-15-minute recovery; run quarterly game days.
- Enforce cost-allocation tagging policy (team, domain, environment, project) on every cloud resource; publish baseline cost report and per-model / per-use-case attribution; author the Cost Optimization Playbook.
- Chair the Change Advisory Board — lineage gate, audit trail, centralized tracking; impact-assess every system / schema change before approval.
- Publish and maintain the platform reference architecture and Architecture Decision Records (ADRs); chair the Architecture Review Board.
- Advise leadership on build vs buy across feature store, catalogue supplements, observability, and GenAI tooling.
- Mentor tech leads across data, ML, AI, and service engineering on platform standards; influence without authority — your designs ship because they are pragmatic, not because they are mandated.
Requirements
- Bachelor's or Master's degree in Computer Science, Engineering, or a related discipline.
- 8+ years in data / cloud engineering, with 4+ years in architect or staff / principal-equivalent roles owning
- platform-wide standards.
- Deep cloud experience on at least one major hyperscaler (Azure strongly preferred; AWS / GCP transferable for the right candidate).
- Production experience with Databricks or equivalent lakehouse (Snowflake, BigQuery).
- Terraform at scale — module design, state management, drift handling, environment promotion.
- CI / CD for data systems — notebook deployments, pipeline configs, schema migrations, blue / green for data jobs.
- FinOps leadership — owned a cost-reduction target with measurable, attributable results.
- Strong on IAM, networking, encryption, secrets management in regulated cloud environments; can author crisp ADRs and chair an Architecture Review Board.
Preferred Qualifications
- Multi-cloud production experience and / or platform-engineering background (internal developer platforms, golden paths).
- Data Mesh / data-as-a-product implementation at scale; streaming architecture (Kafka / Event Hubs, Flink, Spark Streaming).
- Regulated-industry experience (retail PDPA, finance, healthcare); AI workload capacity planning (GPU, vector DB, LLM cost modelling).
- Vendor certifications such as HashiCorp Terraform Associate / Professional, Azure Solutions Architect Expert, or Databricks Solutions Architect.