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.