обновлено 5 дней назад
Senior Data Engineer
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): Designing and building greenfield cloud-native data platforms, real-time pipelines, and data products for enterprise and government clients with an accent on data mesh, data products, data contracts, and production-scale architecture. Focus on streaming systems, large-scale data processing, secure governance, performance optimization, and technical leadership in consulting engagements.
Location: London, England, United Kingdom; Workplace: Hybrid
Company
is an independent technology consultancy that designs and builds modern data platforms, intelligent systems, and bespoke software for enterprises, scale-ups, and government clients.
What you will do
- Own the end-to-end architecture and technical direction of modern, cloud-native data platforms.
- Design and deliver greenfield data platforms, data products, data mesh architectures, and data contracts using Databricks, Snowflake, AWS, and GCP.
- Build and optimize batch, real-time, streaming, and event-driven pipelines with Kafka, Flink, Kinesis, Pub/Sub, Airflow, Dataflow, and Glue.
- Process large datasets with Spark and Flink while optimizing storage, access patterns, and production performance.
- Work directly with clients to translate business needs into pragmatic engineering decisions and technical solutions.
- Set engineering standards, review designs and code, mentor engineers, and improve data quality, testing, observability, security, and operational excellence.
Requirements
- Senior-level hands-on engineering experience with ownership of large-scale data platform architectures.
- Strong Python and SQL skills, with deep experience in Spark and modern data platforms such as Databricks or Snowflake.
- Solid experience with AWS or GCP cloud data services and large-scale production data pipelines.
- Strong data modeling and architectural decision-making skills, including performance, cost, and complexity trade-offs.
- Experience with relational, NoSQL, and analytical storage technologies and formats.
- Experience with infrastructure as code, CI/CD, data testing, and quality tools such as Terraform, Pulumi, GitHub Actions, ArgoCD, dbt, Great Expectations, or Soda.
Nice to have
- Experience in consulting or professional services environments.
- Experience mentoring senior engineers and influencing technical culture.
Culture & Benefits
- Work on interesting, high-impact data and technology problems.
- Build modern platforms rather than maintain legacy systems.
- Collaborate with experienced senior engineers.
- Autonomy, influence, and opportunities for professional growth.
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