Overview:

This is a ground floor opportunity to build a data platform from scratch inside a specialist technology led advisory firm working across energy, aviation, transport and water. The firm pairs advanced mathematical optimisation and machine learning with deep sector expertise to solve complex operational problems in technically demanding markets. As Senior Data Engineer, you will set the technical direction for the platform and contribute to the pipelines feeding on demand optimisation models.

The team is small, flat and technically strong, suited to someone who wants ownership rather than a seat in a big hierarchy. You will work closely with consultants, engineers and stakeholders to turn ambiguous data needs into solid, well tested solutions. The firm is known for rigorous, high stakes analytical work where accuracy is non negotiable.

Responsibilities:

- Lead the technical design and architectural direction of the data platform, owning its vision as it matures from early stage foundations
- Build and maintain pipelines that source, clean and structure data feeding optimisation and modelling work, including external market and regulatory data
- Set the standard for data engineering practice across the firm, including data quality, testing and monitoring
- Collaborate with stakeholders across the business to translate ambiguous requirements into effective, production ready data solutions




- Structure and document data models so they can be reused reliably across multiple client engagements

Required Experience:

- Strong SQL and hands on data modelling experience, ideally with dbt, version controlled models, testing and documentation
- Robust Python for ingestion and transformation pipelines
- Experience building ELT pipelines using an ingestion tool such as Airbyte, Fivetran or dlt, paired with a workflow orchestrator such as Airflow, Dagster or Prefect
- Experience with a cloud data warehouse such as Snowflake, BigQuery or PostgreSQL
- Solid software engineering fundamentals including version control, testing, CI/CD and documentation
- Experience with data quality and validation tooling such as dbt tests or Great Expectations
- Comfort working with ambiguous data and confidence chasing requirements independently
- Clear communicator able to work with non technical stakeholders
- Exposure to energy markets, mathematical optimisation or machine learning is highly regarded but not required

Qualifications:

- Bachelor's degree in computer science, software engineering, data science, mathematics or a related quantitative discipline
- Postgraduate qualification in a data or quantitative field is an advantage but not essential
- Relevant cloud or data platform certifications, such as Snowflake or a major cloud provider, are well regarded

📌 Senior Data Engineer - Energy (Sydney)
🏢 ConnectYou
📍 Sydney