Smart Working
Smart Working
Smart Working — бизнеске әлемнің түкпір-түкпірінен мұқият тексерілген әзірлеушілерді тарту арқылы бағдарламалық жасақтама әзірлеу топтарын құруға көмектесетін рекрутинг қызметі. Іріктеу үдерісі техникалық бағалауды және тексеруді қамтиды, ал компаниялар бағдарламалау тілдері мен фреймворктердің алуан түрінде тәжірибесі бар әзірлеушілермен сәйкестендіріледі. Smart Working консалтинг, денсаулық сақтау және маркетинг сияқты салалардағы ұйымдарға икемді, қашықтан жұмысқа қабылдауды қолдап, рекрутинг пен операциялық шығындарды басқара отырып, әзірлеу мүмкіндіктерін кеңейтуге көмектеседі.

Senior Python Data Engineer at Smart Working (Remote, India)

Build Python data pipelines, APIs, and backend services on AWS. Keep production systems dependable with Kubernetes, PostgreSQL, and search and NoSQL databases.

Сипаттама

  • Create and operate dependable Python data pipelines on AWS.
  • Develop and maintain backend services and APIs with Django and FastAPI.
  • Design data models and queries, and improve performance across PostgreSQL and search and NoSQL stores such as OpenSearch, Elasticsearch, and DynamoDB.
  • Deploy and operate Kubernetes services in coordination with the DevOps engineer.
  • Take assigned work from design through testing, review, release, and production support.
  • Work autonomously while coordinating infrastructure and releases with engineering and DevOps/SRE colleagues.
  • Protect data quality and correctness through thorough testing.
  • Use code reviews and CI/CD practices while responding to shifting priorities.
  • Spot issues early, recommend fixes, and question technical choices when needed.
  • Put careful execution, reliability, and production stability first.

Талаптар

  • At least six years in software engineering, including five or more years of professional Python development.
  • Five or more years building Python backend systems.
  • At least three years working on data pipelines and engineering, including ETL/ELT and batch workloads.
  • Experience with orchestration tools such as Airflow, Dagster, Prefect, AWS Glue, or Step Functions.
  • Three or more years using AWS to build and maintain cloud backend services and data pipelines.
  • Strong GCP or Azure experience may be considered individually.
  • At least three years with Python web frameworks, preferably Django or FastAPI; Flask is also acceptable.
  • Three or more years using PostgreSQL for data modelling, querying, and performance tuning.
  • MySQL or SQL Server may qualify when supported by strong SQL expertise elsewhere.
  • At least two years with search or non-relational databases, including Elasticsearch, OpenSearch, or DynamoDB.
  • MongoDB, Redis, or Cassandra are relevant alternatives.
  • At least two years deploying and operating services on Kubernetes.
  • Docker experience with ECS or EKS may be considered as an alternative.
  • Can independently carry technical work from design through implementation, testing, release, and production support.
  • Strong focus on data accuracy, testing, and dependable production systems.
  • Able to collaborate with engineering and infrastructure teams, while offering solutions and questioning decisions when appropriate.
  • Can follow established engineering practices and adjust as priorities change.
  • Preferred: one or more years using Airflow or a similar workflow orchestration tool.
  • Preferred: one or more years with streaming or event processing tools such as Kafka, Kinesis, or SQS.
  • Preferred: one or more years with infrastructure as code and CI/CD, including Terraform and GitHub Actions.
  • Previous experience leading a technical project or owning a data pipeline or backend service from start to finish.

Артықшылықтар

  • Full-time position intended for the long term.
  • Remote-first work setup.
  • A community that supports growth and well-being.
  • Work with international teams and products.
  • Support for personal and career development.
  • Ongoing long-term opportunity, subject to confirmation.

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