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Responsibilities
- Data Engineering pipeline design and implementation experience within a commercial environment.
- Deliver robust data solutions for complex, enterprise-level environments.
- Experience working with metadata-driven ELT/ETL frameworks and modern data orchestration tools.
- Develop data processing solutions using Python, Scala or Java code for large-scale, cloud-based data warehouses that make use of big-data frameworks like Spark, Kafka, etc
- Previous experience in working with legacy data warehouses and reverse-engineering designs from undocumented code.
- Write and optimize complex SQL queries to efficiently process large datasets.
- Demonstrated experience in breaking down complex problems and projects into manageable goals.
- Build and maintain dbt models, tests, and documentation as part of a modular transformation layer.
- Work with data quality engineer - to implement and enhance data quality checks, anomaly detection, validation frameworks, and automated reconciliation processes.
- Design and maintain automated alerting and monitoring for pipelines, data drifts, and upstream failures.
- Deploy and manage applications and data services on Kubernetes (K8s) in collaboration with DevOps/SRE teams.
- Support BI and analytics teams by enabling accessible, trusted, and well-modeled data for reporting and dashboards.
- Work within a scrum-based agile environment, breaking down complex projects into actionable tasks
Technical and Functional skills
- Solid experience with agile methodologies (Kanban, Scrum).
- Strong hands-on experience in:
- dbt (development, testing, documentation, deployment) - Nice to have.
- SQL for advanced analysis and handling multi-terabyte datasets
- Data quality frameworks, reconciliation logic, and validation patterns
- Alerting/monitoring systemsCloud, Grafana, Airflow alerts, etc.)
- Kubernetes app deployment and containerized workflows
- Flexible, resilient, and passionate about delivering high-quality data solutions.
- Excellent organizational and time management skills; ability to prioritize effectively.
- Strong professionalism, confidentiality, and reliability.
- Exceptional interpersonal skills and the ability to build strong relationships across teams.
- Experience collaborating with remote or distributed teams.
- A genuine interest in exploring new technologies and continuously improving engineering practices.
Seniority Level
Mid-Senior level
Employment type
Full-time
Job function
Information Technology
Industries
Gambling Facilities and Casinos
Senior Data Engineer in Melbourne employer: FDJ UNITED
FDJ UNITED is an exceptional employer that fosters a dynamic and inclusive work culture, perfect for Senior Data Engineers looking to make a significant impact in the gambling industry. With a strong emphasis on employee growth, we offer continuous learning opportunities and the chance to work with cutting-edge technologies in a collaborative environment. Located in a vibrant area, our team enjoys a flexible work-life balance and the support of a passionate community dedicated to delivering high-quality data solutions.
