Top Data Jobs in Sydney

Validate invoices and manage energy retailers; maintain sustainability data and reporting; monitor and optimise operational energy; prepare tailored financial reports, accruals, budgeting and forecasting; engage stakeholders and deliver data-driven insights using Excel.

Provide sales team administration across quote-to-cash activities: generate quotes and purchase orders, validate pricing and terms, maintain vendor relationships and pricing, capture data, produce reports, file and manage sales documentation, and recommend process improvements.

Intelligen is seeking Data Engineers with 3-5+ years of experience in ETL and DWH technologies, particularly with Snowflake and dbt, to improve client data models and pipelines.

The Engineering Lead will oversee the APAC Data Engineering Platform team, responsible for developing a scalable data platform, leading team development, collaborating with stakeholders, and ensuring high engineering standards.

Lead design and delivery of scalable data and AI platforms across Azure and Databricks. Architect production-grade ML/LLM solutions (RAG, agentic patterns), build batch and streaming pipelines, formalize medallion/lakehouse standards, implement MLOps/DataOps (CI/CD, monitoring, orchestration), embed Responsible AI and governance, and provide technical leadership, mentoring, and cross-functional delivery.

Lead product strategy and delivery for Fund Accounting and Administration data and reporting across APAC. Define data models, distribution strategies, and client reporting experience. Drive AI-enabled reporting platforms, data governance, and cross-functional initiatives to improve accuracy, automation, and client self-service while managing vendor relationships and risk.

Build and productionize ML systems for personalization, search, and recommendations. Apply statistical and ML models using Python and SQL, collaborate with stakeholders, and measure business impact across cloud environments.

Analyze large datasets to identify trends and deliver actionable insights; design and monitor KPIs; build and maintain dashboards and reporting frameworks; conduct ad hoc analyses; ensure data quality and support reporting infrastructure in partnership with product and business teams.

Work directly with B2B SaaS customers to onboard, structure, and improve product data. Build simple POCs, drive adoption and satisfaction, support renewals, identify expansion, and feed customer insights to product and engineering.

Abstract and enter clinical data from health records, ensure data quality and confidentiality, use EHR/practice management systems and Microsoft Office, troubleshoot basic access/VPN/MFA issues, and collaborate with clinical teams to support operations.

Lead advanced analytics and ML projects: perform EDA, feature engineering, statistical modeling, and build/optimize production ML and Generative AI solutions (LLMs, embeddings, RAG). Collaborate with engineering and MLOps to deploy and monitor models, create visualizations and dashboards, translate insights for stakeholders, and mentor junior team members.

Lead administration and development of Salesforce NPSP, Marketing Cloud and related supporter systems. Build automations and integrations, manage data governance, support campaign delivery, train users, and improve system reliability and usability.

Lead design, build and optimise enterprise data platform and pipelines (Microsoft Fabric migration, AX ERP modelling, Denodo). Ensure platform performance, governance, incident management, and mentor junior/offshore engineers while driving stakeholder delivery in an agile environment.

Research and verify contact information for evangelical megachurches across the U.S.; collect and maintain structured databases in Excel/Sheets/CRM; identify decision-makers; ensure data accuracy and formatting; remove duplicates; categorize records; produce progress reports and support outreach preparation.

Maintain and build SQL-based reports and dashboards, debug data pipelines, validate joins and business logic, own recurring reporting cycles, develop dbt models and documentation, handle stakeholder requests, and support exploratory analyses and analytics engineering tasks.

The Sr Data Engineer will optimize and refactor data pipelines, manage data ingestion from APIs, and support product engineering teams. Responsibilities include design best practices, enhance the modern data stack, and troubleshoot data issues, ensuring resilience and operational excellence.

The Data Engineer will build and manage scalable data pipelines and databases, collaborate on architecture, and drive data systems towards real-time capabilities in a fast-paced, innovative environment.

Design and maintain scalable data pipelines and real-time streaming systems on AWS, enable ML/LLM-powered customer features, integrate Amazon Bedrock and models into agentic workflows, automate ML lifecycle steps, collaborate with ML, data science, and product teams to ship production-grade solutions.

Lead single-threaded product and technical ownership for Client Intelligence & Data, defining APIs and event-driven architectures to deliver merchant-facing analytics, KPIs, and reports. Drive platform strategy toward AI-driven insights, enforce production reliability and automated QA, champion You Build It You Run It culture, partner cross-functionally to scale multi-tenant analytics capabilities, and prioritize work using evidence-based frameworks.

The role involves owning product feature development, participating in system design, and maintaining software performance in an agile setting.

Lead a unified data and experimentation framework across the company, engaging with core business lines to support data-driven decision-making, while ensuring data quality and governance.

Design, develop, and maintain ELT/ETL Snowflake data warehouse solutions; implement data standards, CI/CD, monitoring, and production support; collaborate with product, business, and vendors; mentor junior developers and improve data engineering practices.

Abstract and enter clinical data from healthcare records, apply clinical operations policies, troubleshoot VPN/MFA access, maintain confidentiality, and provide guidance to less-experienced team members while ensuring data quality and workflow adherence.

The Senior Data Engineer will engineer and improve enterprise-scale data platforms on AWS, design and build end-to-end data pipelines, and optimize data processing solutions using Apache Spark and Python. Responsibilities include data governance, compliance controls, and collaboration with cross-functional teams to support analytics and data integration needs.