Smart Working
Smart Working
Smart Working ir personāla atlases pakalpojums, kas palīdz uzņēmumiem izveidot programmatūras izstrādes komandas no rūpīgi pārbaudītiem izstrādātājiem visā pasaulē. Tā atlases process ietver tehniskos novērtējumus un iepriekšējās darbības pārbaudes, savedot uzņēmumus kopā ar izstrādātājiem, kuriem ir pieredze dažādās programmēšanas valodās un ietvaros. Smart Working atbalsta elastīgu attālinātu darbinieku atlasi organizācijām, kas darbojas, piemēram, konsultāciju, veselības aprūpes un mārketinga jomā, palīdzot tām paplašināt izstrādes kapacitāti un vienlaikus pārvaldīt personāla atlases un darbības izmaksas.

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.

Apraksts

  • 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.

Prasības

  • 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.

Priekšrocības

  • 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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