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

About Smart WorkingAt 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 RoleAs 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.ResponsibilitiesDesign, build and maintain reliable data pipelines in Python on AWSBuild and maintain backend services and APIs using Django and FastAPIModel, query and optimise data across PostgreSQL and search/NoSQL databases, including OpenSearch, Elasticsearch and DynamoDBDeploy and run services on Kubernetes, working alongside the DevOps engineerTake end-to-end ownership of assigned work, including design, testing, code reviews, releases and production supportWork independently on assigned tasks while collaborating closely with the engineering team and DevOps/SRE engineer on infrastructure and releasesMaintain high standards of data quality, correctness and testing while understanding how data pipelines contribute to the wider productFollow established engineering practices, including code reviews and CI/CD, while adapting to changing prioritiesProactively identify problems, propose solutions and challenge technical decisions when necessary rather than simply executing ticketsPrioritise thoroughness, reliability and production stability when developing and maintaining data pipelines and data storesRequirements6+ years of experience in software engineering, including 5+ years of commercial Python development5+ years of Python backend development experience, with strong hands-on engineering capabilities3+ 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 Functions3+ 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 basis3+ years of experience with Python web frameworks, particularly Django or FastAPI. Flask is an acceptable alternative3+ years of PostgreSQL experience, including data modelling, querying and optimisation. MySQL or SQL Server experience may be considered where strong SQL expertise is demonstrated elsewhere2+ years of experience with non-relational or search databases, such as Elasticsearch, OpenSearch or DynamoDB. Relevant alternatives include MongoDB, Redis and Cassandra2+ years of Kubernetes experience, including deploying and running services. Docker combined with ECS or EKS exposure may be considered as an alternativeAbility to independently own technical tasks from design through implementation, testing, release and production supportStrong attention to data quality, correctness, testing and production reliabilityAbility to collaborate with engineering and infrastructure teams while independently proposing solutions and challenging decisions where appropriateAbility to follow engineering practices and adapt to changing prioritiesNice to Have1+ year of experience with workflow orchestration, using Airflow or similar technologies. Alternatives include Celery and cron-based schedulers1+ year of experience with streaming or event-processing technologies, such as Kafka, Kinesis or SQS. RabbitMQ is an acceptable alternative1+ year of experience with Infrastructure as Code and CI/CD, including Terraform and GitHub Actions. Alternatives include Pulumi and GitLab CIPrevious experience leading a technical project or taking complete end-to-end ownership of a data pipeline or backend serviceWe may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.