Data Engineering Leader

7 days ago

Melbourne, Victoria, Australia Bebeedata Full time

Elevate our data strategy and engineering capabilities across teams.
About the Role
We are seeking a Principal Data Engineer to define and lead our data strategy, including data warehousing, ETL/ELT processes, and data platform architecture.
You will partner with the security team to ensure data architecture and governance meet compliance, regulatory, and business requirements.
Review, optimise, and maintain existing databases, queries, and indexes to maximise efficiency and performance.
Establish and champion best practices for database design, data modelling, and query optimisation across teams.
Design, build, and scale robust data pipelines for collecting, aggregating, transforming, and normalising data from multiple sources.
Provide direct leadership, mentoring, and technical guidance to software engineers in product engineering teams.
Act as a thought leader and coach, uplifting engineering teams' data literacy and technical capabilities.
About You
You have demonstrated success in leading data strategy, database architecture, and data pipeline development at scale.
You have experience leading and mentoring engineers.
You have expertise in relational databases (design, optimisation, architecture).
You have familiarity with data platform approaches such as data warehouse, data lake, data mesh, etc.
You have a strong background in data warehousing, ETL/ELT, and distributed data systems.
You're proficient in programming languages commonly used for data engineering.
You have experience with cloud-based data platforms and infrastructure (AWS, GCP, or Azure).
You have familiarity with modern data tools (e.g., Snowflake, BigQuery, dbt, Airflow, Kafka).
Requirements
Bachelor's degree in Computer Science, Mathematics, or a related field.
Minimum 5 years of experience in data engineering, with a focus on leadership and mentoring.
Strong understanding of data warehousing, ETL/ELT, and distributed data systems.
Experience with cloud-based data platforms and infrastructure (AWS, GCP, or Azure).
Familiarity with modern data tools (e.g., Snowflake, BigQuery, dbt, Airflow, Kafka).
Benefits
Flexible work arrangements available.
$5,000 per year for professional development.
$500 per year to design your own WFH setup.
Five days entrepreneurial leave per year to work on side projects.
Paid parental leave.
Volunteer leave.
Three free and anonymous therapy sessions per year.
Regular company activities on Friday afternoons.
2:1 matching for non-profit donations.
Compensation
A$190,000 - A$205,000 + super (dependent on experience).

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