
Tech Data Analyst
2 days ago
Position: Tech 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. - Business Analysis & Critical Thinking,Stakeholder management
- 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.
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