Senior Python Engineer - Data ( Remote, Full-Time) [AS340]

Design, build and maintain reliable data pipelines in Python on AWS.

Build and maintain backend services and APIs using Django and FastAPI.

Model, query and optimise data across PostgreSQL and search/NoSQL databases, including OpenSearch, Elasticsearch and DynamoDB.

Deploy and run services on Kubernetes, working alongside the DevOps engineer.

Take end-to-end ownership of assigned work, including design, testing, code reviews, releases and production support.

Work independently on assigned tasks while collaborating closely with the engineering team and DevOps/SRE engineer on infrastructure and releases.

Maintain high standards of data quality, correctness and testing while understanding how data pipelines contribute to the wider product.

Follow established engineering practices, including code reviews and CI/CD, while adapting to changing priorities.

Proactively identify problems, propose solutions and challenge technical decisions when necessary rather than simply executing tickets.

Prioritise thoroughness, reliability and production stability when developing and maintaining data pipelines and data stores.

6+ years of experience in software engineering, including 5+ years of commercial Python development.

5+ years of Python backend development experience, with strong hands-on engineering capabilities.

3+ years of experience in data pipelines and data engineering, including ETL/ELT processes and batch processing. Relevant technologies include Airflow, Dagster, Prefect, AWS Glue and Step Functions.

3+ years of AWS experience, with practical experience developing and maintaining cloud-based backend services and data pipelines. Strong GCP or Azure experience may be considered on a case-by-case basis.

3+ years of experience with Python web frameworks, particularly Django or FastAPI. Flask is an acceptable alternative.

3+ years of PostgreSQL experience, including data modelling, querying and optimisation. MySQL or SQL Server experience may be considered where strong SQL expertise is demonstrated elsewhere.

2+ years of experience with non-relational or search databases, such as Elasticsearch, OpenSearch or DynamoDB. Relevant alternatives include MongoDB, Redis and Cassandra.

2+ years of Kubernetes experience, including deploying and running services. Docker combined with ECS or EKS exposure may be considered as an alternative.

Ability to independently own technical tasks from design through implementation, testing, release and production support.

Strong attention to data quality, correctness, testing and production reliability.

Ability to collaborate with engineering and infrastructure teams while independently proposing solutions and challenging decisions where appropriate.

Ability to follow engineering practices and adapt to changing priorities.

1+ year of experience with workflow orchestration, using Airflow or similar technologies. Alternatives include Celery and cron-based schedulers.

1+ year of experience with streaming or event-processing technologies, such as Kafka, Kinesis or SQS. RabbitMQ is an acceptable alternative.

1+ year of experience with Infrastructure as Code and CI/CD, including Terraform and GitHub Actions. Alternatives include Pulumi and GitLab CI.

Previous experience leading a technical project or taking complete end-to-end ownership of a data pipeline or backend service