обновлено 6 дней назад
Data Engineer (AI Data Platform)
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
Data Engineer (AI Data Platform): Designing and building high-performance data pipelines and curated datasets for a modern Lakehouse and AI platform with an accent on scalability, data quality, and reliability. Focus on developing robust data assets in production and implementing distributed data processing frameworks to support analytics and AI use cases.
Location: Warsaw, Mazowieckie, Poland; office-based role.
Company
is a global investment banking, securities and investment management firm with offices worldwide.
What you will do
- Build, enhance, and support batch and streaming data pipelines on the Lakehouse and AI data platform.
- Develop raw, refined, and curated datasets for analytics, reporting, and AI use cases.
- Apply data modelling principles covering business entities, relationships, historical change, schema evolution, and compatibility.
- Implement data quality controls, reconciliation processes, testing, monitoring, and issue resolution.
- Optimize data processing through partitioning, clustering, and other performance techniques.
- Collaborate with engineers, platform teams, and data consumers to deliver reliable production data products.
Requirements
- Bachelor’s or master’s degree in a relevant discipline, or equivalent practical experience.
- Strong hands-on programming experience in Python or Java and good working knowledge of SQL.
- Experience building or supporting production data pipelines in a collaborative engineering environment.
- Experience with distributed data processing frameworks such as Apache Spark.
- Knowledge of software engineering fundamentals, including version control, testing, release discipline, and CI/CD.
- Knowledge of JSON, Avro, Parquet, and data design concepts including normalized and denormalized models, natural and surrogate keys.
Nice to have
- Experience with Kafka, Snowflake, Apache Iceberg, Databricks, Hadoop ecosystem technologies, Sybase IQ, or Kubernetes-based deployments.
- Ability to contribute to technical design, platform standards, and delivery approaches across broader use cases.
Culture & Benefits
- Engineering teams build scalable systems and work closely with business and platform users.
- Training and development opportunities support long-term professional growth.
- Benefits include wellness, personal finance, mindfulness, and firmwide network programs.
- Reasonable accommodations are available during the recruiting process for candidates with special needs or disabilities.
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