At a Glance
- Tasks: Analyse and transform messy data into actionable insights for a major financial institution.
- Company: Join a leading financial institution with a focus on innovation and collaboration.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Dynamic role with exposure to various teams and evolving challenges.
- Why this job: Make a real impact by shaping data governance and migration processes.
- Qualifications: 2-4 years as a Data Analyst with strong SQL and Python skills.
The predicted salary is between 64350 - 78650 $ per year.
Experience Junior (0-5 years) | Mid Level (6-10 years)
- Duration 6 Months
- Hybrid
- Sydney, Australia
- Required Skills Merchant Acquiring SQL Data Analysis Python Data Visualisation
- Project Overview
Requirement Description
A major financial institution is seeking a Data Analyst to support the data remediation stream of a large-scale migration program.
This role focuses on analysing customer and merchant data that didn't fit the standard migration process, whether due to hygiene issues, mismatches, missing values or translation rule gaps, and turning the patterns found into purposeful business rules and system logic.
The analyst will play a critical role in shaping how exceptions are handled, both now and in the future.
Working across business, technology, operations and vendor teams, the Data Analyst will convert messy data into clear, actionable recommendations that support migration readiness and data governance.
This is a continuously evolving role that suits someone with analytical sharpness, systems thinking and strong stakeholder skills.
Key Responsibilities
- Conduct deep-dive analysis of customer, merchant, transaction and product data to support migration readiness and identify remediation needs.
- Analyse data anomalies, cluster similar issues together and uncover root causes and recurring patterns.
- Lead data mapping between legacy and target systems, validate source-target mapping, and build and validate migration input files to support phased customer transitions.
- Collaborate with business and technology SMEs to shape decisions, business rules and system logic for exceptions.
- Produce artefacts such as decision papers, rule proposals and remediation prioritisation, and help build future-proofed logic that prevents the same issues recurring.
- Automate data processing pipelines and reporting workflows using Python and SQL, building modular, parameterised scripts for batch processing and auditing.
- Develop migration tracking tools, exception reports, risk flags and interactive dashboards (Power BI, Tableau or Streamlit) to give stakeholders real-time insight into remediation progress and migration waves.
- Partner with product, operations, vendors, risk, compliance and data management teams to ensure data integrity, accuracy and governance compliance, and translate technical outputs into clear, business-friendly documentation.
- Your Background
Essential
- 2-4 years' experience as a Data Analyst or Analytics Specialist in financial services.
- Proven experience supporting data migrations, system transitions or customer remediation programs.
- Experience in regulated environments with strong data controls (banking, insurance, telco, etc.).
- Experience working in a structured, fast-paced environment with multiple stakeholders.
- Advanced Python scripting for automation, ETL, remediation checks and data transformation.
- Expert-level SQL (Teradata, Oracle), including complex joins, CTEs, window functions and query optimisation.
- Experience building dashboards in Power BI, Tableau or Streamlit.
- Advanced Excel/Sheets skills (formulas, pivots, lookups) and proficiency in Git.
- Strong communicator who can present data-driven narratives to non-technical stakeholders, with a structured, organised and proactive approach.
Desirable
- Exposure to AWS Sage Maker.
- Comfort using Jupyter Notebooks for analysis and stakeholder storytelling.
- #J-18808-Ljbffr
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