Location: Sydney Australia Job Description: Senior Data Engineer / Analyst Apply now Job no: 495237 Work type: Full-time Location: PH - Manila Categories: Collections, Information Technology - Take ownership of critical analytics, data processes, and operational workflows - Flexible hybrid work options to support work-life balance - Competitive salary with bonus and strong career development pathways This role is pivotal in supporting our internal analytics capabilities to improve business outcomes across operations, marketing, and lending. You will work across data analysis, reporting, data management, and operational processes, ensuring accuracy, efficiency, and continuous improvement in how data supports the business. You will contribute to maintaining and improving data workflows, supporting reporting platforms, and delivering insights through analysis and modelling. Collaborate with cross-functional teams to enhance processes, automate workflows, and ensure data-driven decision making across the organisation. Key Responsibilities include: - Support internal analytics teams with exploratory data analysis, modelling, and data requests - Maintain and improve data warehouse processes, data management frameworks and operational processes - Support campaign design, execution, automation, and performance analysis across channels (e.g. SMS, letters, digital) - Deliver and maintain reporting solutions (Power BI, Tableau) - Provide frontline support and troubleshooting for reporting tools and systems - Partner with stakeholders and drive continuous improvement across the business What We're Looking For: - Proven experience in data analysis, engineering, or analytics within a commercial environment - Strong SQL, SAS, or Python capability for data analysis, extraction, and modelling - Experience working with cloud-based data platforms (e.g. AWS, Snowflake, Databricks, or similar) - Strong analytical and problem-solving skills, with the ability to work with large datasets - Experience with data visualisation tools (Power BI, Tableau) and reporting frameworks - Degree in Mathematics, Statistics, Engineering, Finance, or a related quantitative discipline What's In It for You? - Complimentary life insurance from day one - HMO coverage from day one, with dependent benefits as your tenure grows - Retirement benefits to support your future - Weekly fresh fruit provided in the office - Engaging company events and recognition programs celebrating your achievements - A strong focus on health and safety, with offices aligned to IATF guidelines - Competitive salary package with incentives - Supportive, people-first culture that promotes work-life balance About Us Credit Corp is Australia's largest provider of sustainable financial services to the credit-impaired consumer segment. We are an ASX-listed company with over 2000 staff across Australia, New Zealand, the USA, and the Philippines. We work closely with regulators to provide sustainable financial solutions aimed at improving our customers' circumstances and enabling financial inclusion. Advertised: 25 May 2026 Singapore Standard Time Applications close: Back to search results Apply now Refer a friend

• Design, build, and maintain scalable batch and streaming data pipelines using Apache Spark and cloud‑native data technologies • Develop and optimize ETL/ELT workflows to ingest, transform, and curate data from diverse source systems into analytics‑ready datasets • Implement data modeling and transformation logic to support reporting, dashboards, and downstream analytical and machine learning workloads • Build and manage data processing workloads within modern lakehouse platforms, including Microsoft Fabric / OneLake (preferred) • Ensure data quality, reliability, and consistency by implementing validation checks, monitoring, and reconciliation processes • Optimize Spark jobs for performance, cost efficiency, and scalability across large and complex datasets • Manage and evolve data schemas while handling schema drift and upstream source changes • Develop reusable frameworks, libraries, and standardized patterns to improve data engineering productivity and consistency • Implement CI/CD pipelines for data workloads to enable automated testing, deployment, and rollback • Monitor data pipelines and jobs, troubleshoot failures, and resolve performance or data quality issues • Partner with analytics engineers, BI developers, and data scientists to understand data requirements and deliver curated datasets • Collaborate with platform, security, and governance teams to ensure data security, compliance, and proper access controls • Contribute to Agile delivery processes, including sprint planning, design reviews, and continuous improvement initiatives

• Design, build, and maintain scalable batch and streaming data pipelines using Apache Spark and cloud‑native data technologies. • Develop and optimize ETL/ELT workflows to ingest, transform, and curate data from diverse source systems into analytics‑ready datasets. • Implement data modeling and transformation logic to support reporting, dashboards, and downstream analytical and machine learning workloads. • Build and manage data processing workloads within modern lakehouse platforms, including Microsoft Fabric / OneLake (preferred). • Ensure data quality, reliability, and consistency by implementing validation checks, monitoring, and reconciliation processes. • Optimize Spark jobs for performance, cost efficiency, and scalability across large and complex datasets. • Manage and evolve data schemas while handling schema drift and upstream source changes. • Develop reusable frameworks, libraries, and standardized patterns to improve data engineering productivity and consistency. • Implement CI/CD pipelines for data workloads to enable automated testing, deployment, and rollback. • Monitor data pipelines and jobs, troubleshoot failures, and resolve performance or data quality issues. • Partner with analytics engineers, BI developers, and data scientists to understand data requirements and deliver curated datasets. • Collaborate with platform, security, and governance teams to ensure data security, compliance, and proper access controls. • Contribute to Agile delivery processes, including sprint planning, design reviews, and continuous improvement initiatives.

• Build and maintain data pipelines across Salesforce, SharePoint, Excel, and operational systems into our StarRocks data warehouse using dbt and Python. • Develop and ship AI agents and copilots using the Claude API (and other LLM tooling) for use cases like lead scoring, account research, call analysis, and internal Q&A over company data. • Design and automate cross-system workflows using Power Automate, Teams Adaptive Cards, and lightweight Python/FastAPI services to replace manual, spreadsheet-driven processes. • Model business data in dbt and Omni — building reusable semantic models, metrics, and dashboards that GTM, RevOps, and leadership rely on. • Enrich and clean prospect and account data using sources like ZoomInfo, LinkedIn Sales Navigator, and public government datasets (e.g., USASpending, SAM.gov, FCC, EIA, FERC, SEC EDGAR). • Prototype and ship internal tools end-to-end — backend (Python/FastAPI), frontend (Vite/React), and storage (PostgreSQL, StarRocks) — for AI-prioritized daily workflows. • Write clear documentation for data models, pipelines, agents, and workflows so the team can extend and maintain them. • Collaborate with GTM, RevOps, Finance, and product teams to translate business questions into data and automation solutions. • Stay current on advances in agentic AI, retrieval, evals, and the modern data stack — and bring useful ideas back to the team.