Data Analyst

Position: Data Analyst

Location: Sydney

Duration: 6 months

Position Summary

We don't sit back and wait for the future to happen—we craft it through new technology, innovation, and investment. As a challenger brand with a challenger spirit, seeking a
Data Analyst
(around 6 years' experience) to support our
enterprise‑wide data lifecycle management
and
data retention
initiatives while delivering high‑quality insights for business stakeholders.

You will work closely with the
Data Product Manager
, solution architects, application owners, and engineering teams to
analyze data structures and application landscapes
, design meaningful
reports and visualizations
, translate requirements into clear backlog items, and help drive compliant, scalable data management patterns across the Optus group.

Key Responsibilities

Data Analysis & Insights

• Perform data extraction, profiling, cleansing, and transformation using
  SQL
  and
  Power BI/Excel
  to produce accurate, trusted datasets.
• Build and maintain
  dashboards, reports, and ad‑hoc analyses
  that provide actionable insights for business and technology stakeholders.
• Present findings clearly—telling the story with data, trends, anomalies, and recommended actions.

Data Lifecycle & Risk Support

• Investigate applications and their data to assess
  retention needs, risks, and compliance
  implications across brands, segments, and channels.
• Map
  data flows and integration points
  between systems; document data lineage, usage, and control gaps with SMEs and application owners.
• Partner with solution architects and product managers to
  evaluate retention and data management solutions
  ; identify opportunities for
  automation
  and process improvement.

Requirements, Documentation & Stakeholder Collaboration

• Lead/participate in requirement‑gathering sessions and workshops; translate outcomes into
  Epics, User Stories, Acceptance Criteria, and Test Cases
  in Jira.
• Maintain clear documentation (source‑to‑target mappings, calculation logic, validation rules, report specs) to ensure transparency and repeatability.
• Engage effectively with cross‑functional teams (engineering, security, risk, legal, business) and manage expectations through structured updates.

Delivery & Agile Ways of Working

• Contribute to
  backlog refinement and prioritization
  , ensuring items are well‑scoped, testable, and aligned to timelines and value outcomes.
• Support and/or facilitate agile ceremonies (stand‑ups, sprint planning, reviews/demos, retrospectives); drive continuous improvement in quality and throughput.
• Validate deliverables against the
  Definition of Done
  and acceptance criteria; drive rigorous
  data quality checks
  and reconciliation.

Quality, Governance & Compliance

• Apply data quality frameworks (completeness, accuracy, consistency, timeliness), define validation rules, and track defects through closure.
• Ensure adherence to
  data policies
  (retention, privacy, information security) and audit readiness with appropriate evidence and artifacts.
• Contribute to standardized metrics and reporting for compliance and delivery governance.

Must‑Have

• 5–7 years
  of experience as a Data Analyst (or similar) in complex enterprise environments.
• Strong
  SQL
  skills (data extraction, joins, window functions, performance basics) and hands‑on experience with
  Power BI
  (data modeling, DAX/Power Query, visuals).
• Demonstrated experience analyzing
  application data structures
  , mapping
  data flows
  , and working with technical SMEs.
• Proven ability to translate ambiguous business problems into
  clear analytical outputs
  and
  backlog items
  (Epics/Stories/AC).
• Excellent documentation, communication, and stakeholder management skills; highly organized, proactive, analytical, and detail‑oriented.
• Working knowledge of
  Agile frameworks
  (Scrum/Kanban) and delivery tools (
  Jira/Confluence
  ).

Nice‑to‑Have

• Exposure to cloud data platforms (e.g.,
  Azure
  ADLS/ADF/Synapse/
  Databricks
  , or AWS/GCP equivalents).
• Awareness of
  data retention/privacy
  (e.g., GDPR principles), data governance, and metadata/lineage tools (e.g.,
  Collibra
  ).
• Experience with
  Python
  for analysis/automation (pandas), and
  Excel
  advanced features (Power Query, advanced formulas).
• Telecom or large‑scale consumer services domain experience.

Education & Certifications

• Bachelor's degree in
  Computer Science, Information Systems, Mathematics, Statistics, Engineering
  , or equivalent practical experience.
• Certifications (nice‑to‑have):
  Microsoft Power BI
  ,
  Azure Fundamentals
  ,
  PSM/CSM
  .

Tools & Technologies

• Data & BI:
  SQL, Power BI (DAX, Power Query), Excel.
• Collaboration & Delivery:
  Jira, Confluence, MS Teams, SharePoint.

(Optional/Plus)
: Python, Azure (ADF/ADLS/Synapse/Databricks), Git.