Senior Synapse & Data Lake Automation Tester
Australian citizenship required. No PR or Work Visa holders. Must be able to obtain Baseline security clearance.
What to Submit
1. A tailored resume in docx format
2. Individual responses to each criterion (max 3000 characters each)
RFQ Details
* RFQ ID: LH-05471
* Agency: Clean Energy Regulator
* Closing Date: Thursday, 05 February 2026 – 11:59pm (Canberra time)
* Estimated Start Date: Sunday, 01 March 2026
* Initial Contract Duration: 12 months
* Extension Term: 12 months
* Number of Extensions: 1
* Experience Level: Senior – EL1 equivalent
* Security Clearance: Must be able to obtain Baseline
* Location of Work: ACT
* Working Arrangements:
Hybrid. Candidates are generally expected to have an office presence at 47 Bowes St, Phillip ACT 2606.
Home-based working arrangements may be considered subject to meeting the buyers policies.
Interstate remote work arrangements will be considered but are less desirable.
* Maximum Hours: 40 hours per week
Job Details
The Clean Energy Regulator seeks to engage one or more Lead Testers with expertise in Azure Synapse and Data Lake environments.
The Lead Tester(s) will be responsible for designing, executing, and governing comprehensive testing strategies for data platform solutions, ensuring delivery quality, risk mitigation, and operational readiness across multiple delivery teams.
Key Duties and Responsibilities
* Test Strategy & Planning: Develop and implement multi-phase, risk-based test strategies aligned to delivery milestones. Set entry/exit criteria, quality gates, and prioritise testing by business risk and data criticality. Negotiate test effort allocation with stakeholders.
* Execution & Governance: Lead disciplined test cycles, enforce gating, manage defect triage, track coverage/readiness, and drive UAT coordination and formal sign-offs. Foster collaboration across delivery teams from a test-driven perspective.
* Stakeholder Communication: Tailor communications for executive and technical audiences, explain trade-offs, escalate issues early, and provide concise status and risk mitigation updates.
* Systems Thinking & Initiative: Rapidly understand solution landscapes, anticipate risks (e.g. schema drift, data freshness), and propose pragmatic mitigations.
* Technical Testing Expertise: Validate end-to-end data platform workflows (ingestion, transformation, serving), reconcile control totals, test SLAs/data contracts, and ensure data quality and lineage (completeness, accuracy, timeliness, uniqueness, conformity).
* Performance & Cost Awareness: Plan and interpret performance/load tests, tune resources (DWU/Spark pools), and identify bottlenecks.
* Operational Readiness: Implement observability (logs, metrics, alerts), validate retries/rollback, design smoke/canary tests, and prepare runbooks.
* Framework & Automation: Build reusable test frameworks, embed automation in CI/CD pipelines, and design runtime health/SLA monitoring solutions.
Selection Criteria
The buyer has specified that each candidate must provide a response to each criterion. Each response is limited to 3000 characters.
Essential criteria
1. Risk-based Test Strategy & Planning – Designs multi-phase, risk-based strategies aligned to delivery milestones; sets entry/exit criteria and quality gates; prioritises by business risk and data criticality; negotiates test effort allocation with business stakeholders based on identified priorities.
Evidence: Test Strategy document; detailed test plan; risk register; prioritisation matrix.
Execution & Governance – Runs disciplined cycles; enforces gating; leads defect triage; tracks coverage and readiness; drives UAT coordination and formal sign-offs; leads collaboration across multiple delivery teams from a test-driven perspective.
Evidence: Cycle schedules; triage minutes; dashboards; UAT sign-off records; examples of cross-team coordination.
Communication & Stakeholder Management – Tailors communications for executives versus engineers; explains trade-offs; escalates early; provides concise readiness/status and risk mitigation paths.
Evidence: Status packs; stakeholder map; negotiation examples; communications artefacts.
Systems Thinking & Initiative – Understands solution landscape with minimal direction; anticipates risks (schema drift, freshness); proposes pragmatic mitigations.
Evidence: Architecture artefacts.
2. End-to-End Platform Testing – Validates ingestion, transformation, and serving; reconciles control totals; tests SLAs and data contracts.
Evidence: End-to-end test cases; reconciliation results; pipeline run history; defect examples.
Data Quality & Lineage – Defines rules for completeness, accuracy, timeliness, uniqueness, conformity; implements drift detection; measures freshness.
Evidence: Data quality rule catalogue; lineage diagrams; data quality reports; schema drift handling notes.
Performance, Scalability & Cost Awareness – Plans load/performance tests; interprets Spark/Synapse metrics; tunes DWU/Spark pools; identifies bottlenecks.
Evidence: Performance test plan; resource/cost analysis; tuning decisions.
Operational Readiness & Observability – Implements logs, metrics and alerts; validates retries/rollback; designs smoke/canary tests; prepares runbooks.
Evidence: Observability approach; alert policies; runbooks; post-incident retrospectives.
Reusable Test Frameworks & Patterns — Builds modular, versioned libraries/templates for schema validation, regression packs, control totals, drift checks; encourages organisation-wide reuse.
Evidence: Code repositories; framework documentation; template packs; versioning strategy.
Automation & CI/CD Integration — Embeds pre/post-deployment checks in pipelines; parameterised tests; environment-aware configurations; treats tests as code; experience using SQL, Synapse and Python to analyse transformation results and automate dataset comparisons.
Evidence: CI/CD pipeline stages; test harness; PR checks; automation scripts in SQL/Python; examples of automated data comparison.
Runtime Health & SLA Monitoring — Designs run-time health checks (canary, anomaly thresholds); dashboards for SLAs/SLOs; alerting and safe remediation.
Evidence: Health dashboards; alert configurations; incident playbooks; SLA breach reports.
Desirable criteria
1. The extent to which the response offers positive social impact.
2. All costs, fees, allowances, and charges associated with the implementation and completion of contract obligations will be assessed broadly to determine any risk.
3. The extent to which the response is a suitable risk level to the Clean Energy Regulator.