Senior Data Engineers (Databricks / Azure) @ Antal

Senior Data Engineers (Databricks / Azure) @ Antal

Polsko

Must have: Solid software engineering and DataSecOps background, including CICD tools

Expertise:

• Minimum 6 years of experience in a Data Engineer role.
• Degree in Computer Science, Statistics, Informatics, Information Systems, or a related field.
• Strong software engineering and DataSecOps background, including proficiency with CI/CD tools.
• Ability to explain complex technical concepts in simple terms.
• Hands-on experience with Databricks, including recent and advanced features.
• Experience with the Microsoft Azure Analytics stack and real-time analytics tools.
• Advanced proficiency in SQL and familiarity with multiple database systems.
• Understanding of data modeling techniques for analytics.
• Strong analytical skills to perform root cause analysis on data and processes.
• Experience with data security operations, preferably within the Azure ecosystem.
• Proven ability to troubleshoot and solve complex data-related issues.
• Awareness of data management frameworks (e.g., DAMA) and exposure to data quality/catalogue tools such as Collibra or Alation (highly desirable).
• Experience in API development and real-time data serving strategies (highly valued).
• Strong verbal and written communication skills in English (C1)

Senior Data Engineers (Databricks / Azure) – Remote

We are looking for 3–4 Senior Data Engineers who are highly proficient in Databricks.
Please note: we are not looking for candidates who have only transitioned from Cloudera, EMR, or similar platforms without upskilling in Unity Catalog and recent Databricks capabilities.

Ideal candidates will have hands-on experience with integration projects or streaming analytics, and a strong software engineering background. You should know how to write unit tests, use Git proficiently, and demonstrate solid expertise in Databricks and Azure Data Factory.

,[Curate structured, semi-structured, and unstructured data by building efficient, cost-effective, and scalable pipelines using Databricks and the Azure Analytics stack., Design, create, and maintain robust data pipeline architectures, ensuring data quality, reliability, and scalability., Assemble and manage large and complex data sets to meet both functional and non-functional business requirements., Identify, design, and implement process improvements, including automation and data delivery optimization., Collaborate closely with Product Owners, Scrum Masters, and Enterprise Data Management leadership to deliver high-quality data solutions on time., Align with Data Engineering chapter standards and best practices., Mentor and coach team members to achieve engineering excellence., Partner with architects to design robust, scalable, and cost-efficient data solutions.] Requirements: Degree, CI/CD, Databricks, Microsoft Azure, SQL, Analytical skills, Data management, Collibra, Alation, API

Kategorie

data

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