2 дня назад
Senior Data Engineer (Python/Spark)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Data Engineer (Python/Spark): Owning and operating large-scale data and feature pipelines powering recommendation and advertising machine learning systems with an accent on reliability, data quality, and production operations. Focus on processing billions of daily events, troubleshooting complex data issues, and supporting scalable ML experimentation within strict SLAs.
Location: Work from the European Union region; Sweden is specified as the location. A valid work permit is required.
Company
is a global AI-first digital transformation and engineering partner delivering data, cloud, automation, and digital product solutions.
What you will do
- Own and operate data and feature pipelines supporting recommendation and advertising ML systems.
- Ensure reliable ingestion and processing of billions of daily events through monitoring, data-quality checks, and backfills.
- Provide dependable production and experimental data for Data Scientists and Analysts.
- Take over ongoing pipeline and platform initiatives and maintain delivery momentum.
- Troubleshoot production data issues and keep the platform stable within SLA requirements.
- Maintain documentation and runbooks for effective knowledge transfer.
Requirements
- Several years of hands-on Data Engineering experience and the ability to work independently from day one.
- Strong programming skills in Python, SQL, and Spark, with experience building and operating large-scale ETL/ELT pipelines.
- Hands-on experience with Airflow or a similar orchestration tool.
- Experience with GCP; AWS or Azure experience is also acceptable.
- Strong software engineering fundamentals, including Git, CI/CD, testing, and maintainable code.
- Eligibility to work from the European Union region and a valid work permit are required.
Nice to have
- Experience with feature stores or production ML data pipelines.
- Hands-on experience with BigQuery.
- Exposure to recommendation systems, ranking, or advertising data.
Culture & Benefits
- Work in a people-first engineering culture focused on technical excellence and continuous growth.
- Collaborate with Data Scientists, Analysts, and Engineering teams.
- Contribute to projects involving modern cloud and data technologies, including AWS, Azure, GCP, Databricks, and Snowflake.
- Participate in knowledge sharing across an international engineering organization.
Hiring process
- CV review.
- HR call, interview, and client interview.
- Final decision.
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