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Role Description: The Data Products Practice Lead will be responsible for establishing and growing a Data Products capability focused on the Australian Banking and Financial Services sector.

The role will help clients transition from traditional data delivery models to a product-led approach based on clear business ownership, reusable and governed data products, self-service consumption and measurable value realisation.

The Practice Lead will combine data strategy, operating-model design, business consulting, solution shaping and practice development. The role will work closely with banking stakeholders, Data Product Owners, domain teams, governance functions, architects and engineering teams to translate data strategy into executable Data Product initiatives.

The role will also support client pursuits, maturity assessments, transformation roadmaps, solution development and the creation of reusable Data Product frameworks and accelerators.

Location: Sydney

Salary: AUD 235,889– 250,588 Annual Gross

Please Note: - The above salary range is only indicative and maybe subject to suitable enhancements, based on internal company processes

Flexible working arrangements (hybrid, reviewed case-by-case basis). Feel free to connect with your recruiter to learn more about how this works in practice.

Roles And Responsibilities

- Establish and lead the Data Products Practice for Banking and Financial Services, including its strategy, service offerings, delivery methods and capability roadmap.
- Advise banking clients on Data Product strategy, domain ownership, product operating models, funding models and federated governance.
- Conduct Data Product maturity assessments covering ownership, product management, data quality, discoverability, platform capability, reuse and business adoption.
- Develop prioritised transformation roadmaps and business cases for the design, delivery and scaling of Data Products.
- Facilitate executive and stakeholder workshops to identify priority business domains, consumer needs, Data Product opportunities and measurable outcomes.
- Shape Data Products across banking domains such as Customer, Financial Crime and Fraud, Credit Risk and Lending, Finance and Regulatory Reporting, Payments, Servicing and Operations.
- Define Data Product lifecycle practices covering ideation, prioritisation, design, development, publication, consumption, enhancement and retirement.
- Define roles and responsibilities for Data Product Owners, domain teams, data stewards, platform teams,



governance functions and product consumers.
- Develop governance approaches covering data contracts, quality standards, metadata, lineage, access controls, privacy, security and regulatory requirements.
- Define self-service capabilities, including data marketplaces, catalogues, semantic layers, access-request processes, user guardrails and enablement.
- Establish adoption and value-realisation measures covering product usage, reuse, time to market, data quality, self-service, consumer satisfaction, cost and attributable business value.
- Work with architecture and engineering teams to translate Data Product strategies into scalable solutions across platforms such as Databricks, Snowflake, Microsoft Azure/Fabric and AWS.
- Define reusable frameworks and accelerators, including maturity models, Data Product canvases, data contract templates, operating-model blueprints, adoption playbooks and value scorecards.
- Shape proposals, client presentations, points of view, solution approaches, delivery plans and commercial models for Data Product engagements.
- Support the mobilisation and governance of multidisciplinary Data Product delivery teams across consulting, governance, architecture, engineering, quality and business change.
- Build relationships with platform and technology partners and support joint go-to-market opportunities.
- Develop internal capability through mentoring, training, reusable assets, thought leadership and sharing of delivery experience.
- Represent the practice in client conversations, industry forums and internal leadership reviews

Key Skills And Attributes

- Strong understanding of Data Products, Data Mesh principles, domain-oriented ownership and federated data governance.
- Demonstrated capability in Data and Analytics strategy, operating-model design and transformation roadmap development.
- Good understanding of banking data domains, business processes and regulatory data-management expectations.
- Ability to connect business outcomes, consumer needs, governance requirements, architecture and engineering delivery.
- Strong knowledge of Data Product management concepts, including product vision, consumer personas, product backlogs, roadmaps, lifecycle management, service levels and value measurement.
- Understanding of contemporary data-platform capabilities across Databricks, Snowflake, Microsoft Azure/Fabric or AWS.
- Knowledge of data governance, metadata management, data quality, lineage, catalogue, access management, privacy, security and observability.
- Strong consulting and problem-solving skills, with the ability to structure ambiguous business and technology challenges into practical actions.
- Strong stakeholder-management skills and the ability to influence senior business, technology, risk and governance stakeholders.
- Ability to facilitate executive workshops and communicate complex Data Product concepts in clear business language.
- Strong proposal-development and solution-shaping capability, including the ability to define scope, outcomes, delivery approach, assumptions and dependencies.
- Commercial awareness and the ability to support business cases, estimation, staffing models and outcome-oriented engagement structures.
- Ability to build and lead multidisciplinary teams across business consulting, product management, governance, architecture and engineering.
- Strong written and verbal communication skills, with the ability to prepare executive-level presentations, roadmaps and recommendations.
- Pragmatic and outcome-oriented approach, with a focus on adoption,



reuse and measurable value rather than technology implementation alone.

Essential

- Extensive experience in Data and Analytics consulting, transformation, architecture, product management or related leadership roles.
- Demonstrated experience defining or implementing Data Product strategies, operating models or Data Mesh-aligned capabilities.
- Experience working within Banking, Financial Services or another highly regulated industry.
- Experience engaging senior business, technology, data, risk and governance stakeholders.
- Demonstrated experience facilitating discovery sessions, maturity assessments and operating-model workshops.
- Experience translating strategic recommendations into executable roadmaps, delivery initiatives and measurable outcomes.
- Practical understanding of modern cloud data platforms such as Databricks, Snowflake, Microsoft Azure/Fabric or AWS.
- Strong understanding of data governance, quality, metadata, lineage, security and regulatory considerations.
- Experience shaping client proposals, transformation programs, advisory engagements or Data Product delivery initiatives.
- Experience leading cross-functional teams operating across consulting, product management, architecture, governance and engineering.
- Bachelor’s degree or equivalent professional experience in Information Technology, Data and Analytics, Engineering, Business, Finance or a related discipline.
- Relevant certifications in Databricks, Snowflake, Microsoft Azure, AWS, data management, data governance or product management would be advantageous.
- Excellent customer-facing, written and verbal communication skills.
- Strong attention to detail, analytical thinking and structured problem-solving capability.

ADDITIONAL

- Excellent customer-facing skills
- Excellent written and verbal communication skills
- Strong attention to detail and outstanding analytical and problem-solving skills.

In addition to compensation aligned with your role, you’ll have access to a wide range of perks that support your health, career growth, and overall well-being (AU)

- Income Protection Insurance
- Paid Parental and Volunteer leaves
- Employee Assistance Program (EAP)
- Flexible working arrangements (hybrid, reviewed case-by-case basis)
- Health Insurance Discount and Well-being Program
- Access to Fitness and Gym Memberships
- Salary packaging and novated leasing

Our recruitment and selection process is designed to create the best match for both you and Infosys. Depending on the role, it may include an initial screening, technical or functional interviews, and conversations focused on cultural alignment and shared values. We are committed to making the experience transparent, respectful, and engaging at every step.

Hear from our recruiter on their experience working with Infosys as an Employer

At Infosys, we recognize that everyone has individual requirements. If you are a person with disability, illness, or injury and require adjustments to the recruitment and selection process, please contact our Recruitment team for adjustment either via the following email [email protected] or call 1-(phone hidden). Alternatively, you can include your preferred method of communication in email, and someone will be in touch.

Please note in order to protect the interest of all parties involved in the recruitment process, Infosys does not accept any unsolicited resumes from third-party vendors. In the absence of a signed agreement, any submission will be deemed as non-binding and Infosys explicitly reserves the right to pursue and hire the submitted profile. All recruitment activity must be coordinated through the Talent Acquisition department.

“All aspects of employment at Infosys are based on merit, competence and performance. We are committed to embracing diversity and creating an inclusive environment for all employees. Infosys is proud to be an equal opportunity employer.”

📌 Data Practice Program Manager (Sydney)
🏢 Infosys
📍 Sydney