2 дня назад
Lead Big Data Engineer (Databricks + AWS)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Lead Big Data Engineer (Databricks + AWS): Designing and developing scalable data platforms on AWS with an accent on Lakehouse architectures and real-time data processing. Focus on building optimized batch and streaming pipelines, defining architectural best practices, and mentoring engineering teams.
Location: Poland (Remote/Office)
Company
is a global digital transformation company providing comprehensive software development and data analytics services.
What you will do
- Design and optimize scalable data solutions on AWS using Databricks, Delta Lake, and Unity Catalog.
- Develop batch and real-time processing solutions with Apache Spark, Flink, Kafka, and Kinesis.
- Lead data integration and migration activities, including source-to-target mapping across multiple data sources.
- Drive data platform architecture and engineering best practices to ensure scalability and maintainability.
- Collaborate with business and technical stakeholders to translate requirements into implementation roadmaps.
- Mentor data engineering teams and manage automated workflows via Airflow, MWAA, and Databricks Workflows.
Requirements
- Proven experience as a Lead Data Engineer delivering scalable data platforms and pipelines.
- Hands-on expertise with Apache Spark, Flink, Kafka, Amazon MSK, or Kinesis.
- Strong proficiency in AWS and Databricks (Delta Lake, Unity Catalog, Workflows).
- Advanced SQL skills combined with proficiency in Python, Scala, or Java.
- Experience building and orchestrating data workflows using Airflow, MWAA, or Databricks Workflows.
- English: Upper-intermediate (B2) or higher required.
Nice to have
- Practical knowledge of Snowflake and Amazon Redshift.
- Familiarity with Avro, GitHub, and SQL-based version control systems.
Culture & Benefits
- Collaborative and innovation-driven engineering environment.
- Opportunity to work with cutting-edge technologies in the Databricks ecosystem.
- Active knowledge sharing within the professional engineering community.
- Commitment to diversity and equal opportunity employment.
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