Find your next opportunity
Browse fresh openings from leading companies and apply with a resume tailored to the role.
Browse expert rolesBrowse expert rolesBrowse fresh openings from leading companies and apply with a resume tailored to the role.
Browse expert roles13640 openings
4233-4240 of 13640Smart Working
Free to start · No card · 5 credits the moment you sign up
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.
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 (subject to confirmation), 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.
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
Originally posted on Himalayas
Start with a role or skill you want to use in your next job. Use the location and role filters to narrow the results, then open a listing to review the description. A title alone rarely explains the level of responsibility, working arrangement, or experience a team needs. Compare those details before deciding which opportunities deserve a tailored application.
Employers use different titles for similar work. If an exact phrase produces no results, try a shorter title, a core skill, or an alternative name for the role. Remove one filter at a time to understand which requirement is narrowing your search. A broader search can reveal suitable work without asking you to change your actual qualifications.
For each promising listing, read the responsibilities and separate essential requirements from preferences. Note the location, schedule, employment type, and compensation when provided. Missing details are questions to confirm with the employer. A remote opening may still require a particular country, work authorization, or time-zone overlap, so check the full posting before treating it as a location-independent opportunity.
Choose a few examples that demonstrate the skills this employer names. Explain your contribution and its outcome, using accurate numbers where available. Put the most relevant experience first and keep your resume easy to scan. Avoid adding technologies, qualifications, or achievements simply because they appear in a description. Your application should make your existing strengths easier to understand.
Follow the employer’s instructions for resumes, cover letters, work samples, and screening questions. Review the exported file before submitting it: confirm that contact details are correct, text can be selected, and links reach the intended pages. A resume check can help you spot unclear writing before you apply. Its feedback is advisory and does not predict a hiring decision.
Listings are collected from external sources and may change after they appear here. The employer or recruiting destination controls whether applications are open. If an original link is unavailable, check the company’s careers page for the title or move to another opening. An employer website link is a place to check current vacancies, rather than confirmation that a particular job is still accepting applications.
Keep a simple record of the company, role, job reference, application date, and documents you sent. Record any follow-up instructions and the next action you plan to take. This makes it easier to prepare for interviews, compare opportunities, and avoid applying repeatedly to the same opening through different boards. Review your shortlist as employers update their listings and prioritize opportunities with clear requirements that match the work you want to do.