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

About the role

About Smart Working

At Smart Working, we believe your job should not only look right on paper but also feel right every day. This isn’t just another remote opportunity - it’s about finding where you truly belong, no matter where you are. From day one, you’re welcomed into a genuine community that values your growth and well-being.

Our mission is simple: to break down geographic barriers and connect skilled professionals with outstanding global teams and products for full-time, long-term roles. We help you discover meaningful work with teams that invest in your success, where you’re empowered to grow personally and professionally.

Join one of the highest-rated workplaces on Glassdoor and experience what it means to thrive in a truly remote-first world.

About the Role

As a Senior Python Engineer (Backend / Data), you will join an existing engineering team to strengthen backend development and data engineering capabilities. This is a long-term, ongoing opportunity, focused on building and maintaining reliable production systems.

You will work closely with the engineering team and an existing DevOps/SRE engineer on infrastructure, deployments and releases. The role requires independent ownership of assigned work, collaboration across engineering functions and an understanding of how data pipelines support the wider product.

You will contribute to engineering decisions, maintain high standards of data quality, correctness and testing, and propose solutions rather than simply execute assigned tasks. Reliability and thoroughness in production are key priorities.

Responsibilities -

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

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

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

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

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

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

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

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

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

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