Jobs at Billigence

Design and deliver scalable cloud data pipelines, ETL/ELT and data warehousing solutions. Work hands-on in Snowflake, Databricks and cloud platforms, translate business requirements into technical designs, optimise queries, and engage with stakeholders across client projects and internal initiatives.

Lead requirements elicitation and analysis for BI, data and digital transformation projects. Document business, functional, non-functional and data requirements; run workshops; produce BRDs, user stories, process maps and acceptance criteria. Liaise between stakeholders and technical teams, support solution design, UAT, requirements traceability, change management and project delivery.

Lead enterprise-wide solution architecture (70%) and perform hands-on Java development (30%). Design cloud-native microservices, REST APIs, and event-driven integrations; implement Java/Spring Boot/Spring Cloud services; apply Docker, Kubernetes, CI/CD and DevOps practices; work with relational and NoSQL databases; mentor technical teams and engage stakeholders to drive technology transformation.

As a Senior Data Architect, you'll design and maintain data architectures, lead client engagements, mentor junior engineers, and oversee project execution while ensuring client expectations are met.

Design, develop, and optimise Alteryx workflows to automate data preparation and reporting. Integrate and transform data from databases, APIs, and cloud sources, perform cleansing and validation, and support data quality initiatives. Translate business requirements into technical solutions, produce documentation, mentor peers, and collaborate with stakeholders and technical teams within Agile delivery.

Design, develop, test, and maintain software using languages like Java, Python, C++, or Ruby. Collaborate with cross-functional teams, perform code reviews, debug and troubleshoot systems, produce documentation, stay current with technologies, and mentor junior engineers.

The Data Management Lead will oversee data management initiatives for AI transformation, focusing on data quality, governance, and stakeholder engagement while collaborating with various teams.

The Data Management Lead will oversee initiatives to improve workforce data quality, governance, and operational management, collaborating with multiple teams to establish standards and support data strategy.

Conduct outbound prospecting (calls, email, LinkedIn) to generate qualified meetings for BDMs/AMs across APAC; support event outreach and on-site activities; maintain CRM data; qualify prospects for Snowflake, AI, data governance, and analytics opportunities; hit weekly/monthly outreach targets and progress into BDM or AM roles.

Design and maintain data architectures, build data pipelines, and communicate with stakeholders to enhance data reliability and quality.

The DWH Developer will design and build data warehouse solutions, set up cloud infrastructure, and provide data-driven insights while communicating with stakeholders.

Design and build end-to-end data pipelines on Snowflake using a medallion architecture; develop dbt transformations and tests; implement automated data validations; create Streamlit UIs for user inputs and checks; prepare Power BI reporting outputs; document and hand over solutions to clients while collaborating with stakeholders.

The Senior Data Engineer will build and optimize data pipelines in Azure Databricks, migrate existing pipelines from Azure Synapse, and design scalable data models to support a financial services client's data platform modernization.

The Finance Specialist will manage invoicing and payment processes, handle purchase orders, and continuously improve workflows across European offices.

Senior Data Engineer to support a banking client: design and build Snowflake-based data platforms, implement Iceberg tables, develop dbt models, use AWS (S3, Lambda), create CI/CD pipelines, orchestrate with Airflow. Kafka experience is highly desirable. Initial 6-month full-time contract with hybrid work in Sydney CBD.

The role involves transforming raw data, building data models and Power BI dashboards, maintaining data pipelines, and collaborating with PMs to meet business requirements.