SQL Developer — Payroll Calculation Engine

Role Overview

At WageSafe, we develop a sophisticated payroll compliance engine designed to prevent wage underpayments by accurately handling complex payroll scenarios spanning multiple award types. Our calculations incorporate details such as overtime tiers, minimum guarantees, shift continuity, allowances, and superannuation for thousands of employees.

Operating as an AI-first engineering team, our platform leverages a modern cloud data stack, primarily executing SQL transformations over a cloud data warehouse, orchestrated by Python, all versioned in GitHub and deployed on AWS. We use AI coding assistants like Claude as an integral part of our workflow. As an SQL Developer, you'll be responsible for building, testing, and maintaining transformation logic and data pipelines that power our payroll calculation engine. You will collaborate closely with data engineers, product managers, and QA specialists within a cross-functional platform team.

Why This Position is Critical

The challenge of Australian wage compliance masquerades as a data problem but is fundamentally one of legal exposure. Modern awards involve complex interactions — overlapping overtime tiers and minimum guarantees, shifts spanning midnight, multi-layered allowance triggers, and more. Mistakes at scale lead not just to bugs but to expensive remediation and regulatory risks. Every phase of our workflow demands precise conditional business rules, sophisticated temporal logic, and support for multiple tenant environments. Accuracy and deep domain understanding are essential as your work directly affects employees' pay.

Primary Responsibilities

• Implement features by authoring and sustaining SQL and Python logic to address business requirements and exceptional cases such as shift continuity, overnight shifts, specialized allowances, and specific award overrides.
• Validate correctness by reconciling payroll calculations against prior runs and established baselines, and develop regression test suites covering all supported award variations to prevent unintended breaks due to changes.
• Ensure full auditability by enabling transparent traceability for each calculated payment cent, including the triggered rule, input data, and award version, making determinism and explainability core product features.
• Enhance performance by profiling queries, analyzing execution plans, and optimizing SQL constructs (CTEs, window functions) and warehouse workloads to meet tight batch processing deadlines efficiently and cost-effectively.
• Participate actively in peer code reviews focusing on correctness, efficiency, and compliance with payroll business logic; uphold ownership of all delivered code.
• Oversee deployment via CI/CD pipelines onto AWS, monitor live execution, and investigate discrepancies promptly when they arise.
• Collaborate with the QA team to design and validate automated testing suites that accurately reflect business rules.
• Engage in continuous learning to expand expertise in advanced SQL techniques, payroll domain knowledge, and AI-enhanced development methodologies, sharing insights with the team.

Essential Qualifications and Skills

• Between 2 and 4 years of professional experience developing SQL in production data environments.
• Strong proficiency with SQL features including window functions, common table expressions (CTEs), JOIN strategies, and a solid understanding of complex temporal logic involving intervals, overlaps, boundaries, and timezone/daylight saving intricacies.
• Competency in writing clear, maintainable Python code suitable for testing and collaborative development.
• Experienced in integrating AI-based tools (e.g., Claude, Copilot) as core elements of the development process, with solid judgment to verify and override AI outputs when necessary.
• Daily familiarity with Git and GitHub workflows encompassing branching strategies, pull request management, thorough code review, and continuous integration checks.
• Foundational knowledge of ETL processes including pipeline dependency management, batch failure handling, recovery strategies, and cloud data warehouse concepts.
• Experience tuning query performance through analysis of execution plans and subsequent optimization.
• A testing mindset favoring preventive automated tests before implementing fixes, with prior experience developing or maintaining automated test suites for data transformations.
• Ability to handle ambiguity in award interpretation by proactively seeking clarification rather than making assumptions.
• Effective communication skills and comfort working within Agile/Scrum methodologies.
• Residency or work presence in Sydney, NSW, with a hybrid work model requiring onsite presence three days per week.

Preferred Additional Experience

• Familiarity with payroll, HR, or time and attendance systems, including knowledge of modern awards, enterprise bargaining agreements (EBAs), superannuation, and shift-oriented pay structures.
• Hands-on experience with cloud data platforms such as Snowflake, Databricks, or equivalent cloud warehouses or lakehouses.
• Practical knowledge of transformation and orchestration tools like dbt, Airflow, or Dagster.
• Experience with advanced AI development workflows including agentic coding, AI-assisted code reviews, MCP servers, or building internal tooling leveraging large language models.
• Strong engineering practices involving CI/CD pipelines (e.g., GitHub Actions), automated testing frameworks, and version-controlled schema management.
• Expertise in advanced SQL patterns, including JSON parsing, recursive CTEs, or metadata-driven schema validations.
• Familiarity with software engineering and integration technologies such as REST APIs or .NET (C#).
• Exposure to data visualization platforms including Power BI or Tableau.