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Big Data Architect (Databricks + AWS)
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
Big Data Architect (Databricks + AWS) (Data Platforms): Designing and implementing scalable batch and real-time data platforms and processing solutions on AWS with an accent on data ingestion, orchestration, streaming, and analytics. Focus on building reliable pipelines, integrating Kafka or Kinesis, managing Airflow workflows, and delivering production-ready warehousing solutions with Snowflake or Redshift.
Location: Ukraine; remote or office work
Company
Engineering and Technology role focused on data and analytics solutions.
What you will do
- Design and implement scalable data platforms, pipelines, and processing components on AWS.
- Own end-to-end delivery of batch and real-time data solutions, improving data quality, availability, and time to insight.
- Build data ingestion processes, source-to-target mappings, and onboarding flows for new data sources.
- Orchestrate workflows with Apache Airflow or MWAA, including scheduling, monitoring, and error handling.
- Implement streaming solutions with Apache Kafka, Amazon MSK, or Kinesis.
- Develop data warehousing and analytics solutions using Snowflake or Amazon Redshift, including documentation and data models.
Requirements
- Strong experience designing and building scalable data platforms and pipelines.
- Hands-on expertise with AWS services for data engineering and analytics workloads.
- Proficiency in Python, Scala, or Java, with strong SQL skills.
- Experience with Apache Spark, Databricks, or Flink and practical knowledge of Apache Airflow or MWAA.
- Experience with Apache Kafka, Amazon MSK, or Kinesis and familiarity with Snowflake or Amazon Redshift.
- Upper-intermediate or higher English and effective communication in a global environment.
Culture & Benefits
- Remote or office work format.
- Collaborative engineering environment with interaction across engineering, architecture, and business stakeholders.
- Work on reliable, production-ready data platforms and analytics solutions.
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