This role will be supporting Wisr's ongoing effort to modernise and evolve the data platform as we continue to scale and grow. As a key member of the Data Squad, you will bring strong data analysis, validation, reconciliation, and quality capability, coupled with hands-on experience building data pipelines across platform implementation and migration projects in a Medallion architecture.

You'll play a crucial role in supporting the quality and integrity of our data models and pipelines, helping us to build a world-class data platform that serves the entire organisation.

By collaborating closely with various internal stakeholders including your fellow data engineers, Credit Risk, Product Managers, Developers and cross-functional teams including Operations and Marketing, you will play a pivotal role in ensuring seamless data integration, processing, and analytics.

What You’ll Do: 

• Engage with business stakeholders to gather and translate data requirements into testable acceptance criteria and quality checks within the Data Squad

• Design and build scalable pipelines and data models that support data quality, reconciliation, and trusted insight generation within the Data Squad

• Own and evolve the data stack with a focus on data quality and testing practices, supporting platform delivery (e.g. dbt, SQL, Python, orchestration, reconciliation, validation, observability)

• Ensure high standards of data accuracy, integrity, and reliability — especially during platform migration and implementation in a Medallion architecture

• Develop and maintain robust documentation, schema management, and lineage tracking to ensure transparency and traceability

• Forming a deep understanding of our data processes and helping to improve them through implementing best practices

• Staying on top of any failures and issues in our data systems, troubleshooting, proposing improvements and implementing fixes

With hands-on experience across modern data architectures, in data platform implementation and migration projects, you bring strong skills in data validation, source-to-target reconciliation, and quality testing. You've worked alongside data engineers on platform builds — validating pipelines, testing transformations, and ensuring data integrity before and after cutover. You take pride in being the quality gate between business expectations, engineering delivery, and business outcomes — ensuring what was asked for, what was built, and what is consumed are all aligned.

You are confident working with SQL and Python for data analysis, validation scripts, and automated reconciliation. Experience with modern data platforms such as Snowflake and transformation tools like dbt — particularly dbt tests, schema validation, and data quality checks — is highly desirable. Experience with data visualisation tools such as Tableau or Power BI to communicate findings to business stakeholders is a plus.

You’ll also have: 

• 3+ years working on data platform implementation, migration, or modernisation projects

• Tertiary qualifications in Computer Science, Engineering, or a related technical field

• Demonstrated ability to take ownership of projects, collaborate cross-functionally, and work independently in dynamic environments

• Strong SQL skills — complex queries, reconciliation logic, row counts, sum checks, and data profiling

• Good working knowledge of Python for validation scripts, automated reconciliation, and data profiling

• Hands-on experience with dbt — dbt tests, schema tests, and custom data quality checks

• Experience validating data across platform migrations — source-to-target reconciliation, regression testing, and cutover validation

• Experience with major cloud data warehouse or lakehouse platform (e.g. Snowflake, Databricks, BigQuery)

•Good understanding of ELT/ETL concepts and medallion or layered architectures

• Experience with Tableau, Power BI, or similar visualisation tools

• Ability to work cross-functionally with engineers and business stakeholders