Data Engineer role specializing in Azure & Snowflake at InfoCentric. Leading design and delivery of enterprise - scale data platforms for large organizations.
About the role
- Data Engineer developing scalable data solutions across multi-cloud environments for clients. Mentoring junior engineers while ensuring data quality and promoting best practices within the team.
Responsibilities
- Design, build, and optimise scalable Databricks Lakehouse solutions across AWS, Azure, and GCP
- Develop robust data ingestion, transformation, and orchestration pipelines using Databricks (Spark, Delta Lake, Workflows)
- Build high-quality data models to support analytics, reporting, and AI/ML use cases
- Implement medallion architectures (bronze, silver, gold) and modern data engineering patterns
- Collaborate closely with clients to translate business requirements into well-architected, actionable data solutions
- Support or implement dbt, CI/CD pipelines, Git-based workflows, and engineering best practices
- Ensure strong data quality, governance, lineage, security, and performance optimisation within Databricks environments.
- Work alongside analytics, governance, and AI consultants to deliver cohesive, end-to-end solutions
- Contribute to reusable assets, accelerators, and internal frameworks that strengthen Intelligen’s Databricks capability
- Mentor junior engineers and positively influence client delivery and engineering standards
Requirements
- 4–6+ years’ experience in data engineering or analytics engineering
- Strong hands-on experience with Databricks (Spark, Delta Lake, Workflows), ideally in production environments
- Experience with at least one major cloud platform: AWS, Azure, or GCP
- Strong SQL skills and experience building complex data transformations
- Familiarity with modern data stacks — e.g. Databricks, Snowflake, dbt, cloud data lakes, orchestration tools
- Experience working across the full data lifecycle: ingestion → transformation → modelling → consumption
- Consulting, stakeholder-facing experience, or cross-functional delivery exposure
- Knowledge of DevOps concepts, version control, and/or CI/CD in data environments
- Excellent communication, problem-solving, and collaboration skills
- Sydney-based, with ability to work on-site with clients as required
- A mindset of curiosity, delivery excellence, and continuous learning
Benefits
- Work From Home - Flexible hours
- Training & Development
- Free Food & Snacks
- Many socials and community groups
- Opportunity to drive projects that are of interest to you!
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Principal Data Architect at PointClickCare ensuring coherent and scalable data architecture. Driving unified data direction while collaborating with Engineering Architecture team for AI enablement.
Data Engineer Tech Lead developing data solutions at Carelon. Leading a cross - functional team to optimize data workflows and maintain data integrity.
Lead Data Engineer responsible for evolving Manna’s data infrastructure for drone delivery. Overseeing data architecture and analytics while building scalable data pipelines.
Data Engineer designing, implementing, and optimizing data pipelines for DeepLight AI. Collaborating closely with a multidisciplinary team to analyze large - scale data.
Data Engineer designing and maintaining scalable ETL pipelines at Satori Analytics. Collaborating with teams to deliver high - quality analytics solutions across various industries.
Data Architect responsible for defining enterprise data architecture on AWS and Databricks Lakehouse platforms. Enabling scalable data lakes and enterprise analytics for financial services organizations.
Data Platform Operations Support leading data engineering strategy across projects for EXL. Driving innovation and optimization while collaborating with various teams in the organization.
Manager II leading data engineering projects at Navy Federal Credit Union. Overseeing data governance and quality initiatives while managing engineering teams in a hybrid work environment.
Principal Data Engineer responsible for architecting scalable data pipelines and building high - quality data foundations. Collaborating closely with experts to ensure data readiness for advanced analytics.