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6 дней назад

Middle Data Engineer (Databricks)

Формат работы
remote (Global)
Тип работы
fulltime
Грейд
middle
Английский
b2
Страна
Lithuania
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
Middle Data Engineer (Databricks): Building and maintaining scalable ETL/ELT data pipelines and architectures for structured, unstructured, batch, and real-time data with an accent on data quality, governance, and multi-source processing. Focus on optimizing large-scale pipelines, implementing secure data lineage and access controls, and solving reliability challenges across heterogeneous cloud data environments.

Location: Remote

Company

hirify.global develops IT solutions for clients in the US and European markets and has more than 170 IT professionals.

What you will do

  • Design, develop, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
  • Create data architectures supporting frequent transformations and complex, multi-source environments.
  • Collaborate with data scientists, analysts, and stakeholders to align pipelines with business requirements.
  • Monitor, troubleshoot, and optimize batch and real-time data processing systems.
  • Implement data governance, security, privacy, lineage, access control, and auditability practices.
  • Evaluate emerging data engineering technologies, AI frameworks, and infrastructure improvements.

Requirements

  • At least 2 years of data engineering experience.
  • Experience building automated, scalable data pipelines using ETL/ELT methodologies, including Databricks.
  • Strong Python, PySpark, SparkSQL, and SQL skills.
  • Experience with relational and NoSQL databases, APIs, streaming data such as Apache Kafka, and unstructured formats.
  • Hands-on experience with Apache Spark and at least one cloud platform: IBM Cloud, AWS, Azure, or Google Cloud.
  • Knowledge of Apache Airflow or Dagster, data quality, GDPR/CCPA compliance, encryption, and role-based access control.

Culture & Benefits

  • Remote full-time work.
  • Collaboration with data scientists, analysts, and other stakeholders.
  • Work on technology-enabled solutions for higher education and nonprofit organizations.

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