Senior Data Engineer Central Europe

Zoolatech; Central (LA); On-site; USD 110,000 - 150,000; Full time

Job summary

Zoolatech, a global jewelry manufacturer, is transforming its data platform on Azure PaaS to empower analytics and commercial decision-making. We seek a Data Engineer to design and deliver scalable data pipelines and data products across the enterprise.

You will work with product owners, architects, and stakeholders to translate requirements into technical designs, implement CI/CD practices, ensure data quality, and drive measurable business benefits through reusable data assets.

Qualifications

• 5+ years of experience as a Data Engineer.
• Expertise in Azure Synapse Analytics and SQL Server.
• Advanced proficiency in SQL.
• Experience with Azure Data Factory, Databricks, and PySpark.
• Track record of delivering production-ready data products at enterprise scale.
• Strong analytical skills and ability to translate business requirements into technical solutions.
• Excellent communication skills in English.
• Experience working in Agile/Scrum teams.

Responsibilities

• Design, build, and maintain scalable data pipelines and products on the Azure PaaS data platform.
• Collaborate with product owners, architects, and stakeholders to translate requirements into designs and data models.
• Enable analytics and reporting to support commercial initiatives and operational efficiencies.
• Ingest, transform, and optimize large, complex data sets with emphasis on quality and performance.
• Apply DevOps practices, CI/CD pipelines, and coding best practices for production readiness.
• Monitor and own the stability of delivered data products and drive measurable business benefits.
• Promote a reusable data architecture approach across business verticals.
• Foster innovation by following best practices and exploring new data engineering approaches.

Skills

Strong analytical skills

Excellent communication in English

Agile/Scrum

Tools

Azure Synapse Analytics

SQL Server

Azure Data Factory

Databricks

PySpark

SQL

Job description

Our client is a global jewelry manufacturer undergoing a major transformation, moving from IaaS-based solutions to a modern Azure PaaS data platform. As part of this journey, you will design and implement scalable, reusable, and high-quality data products using technologies such as Data Factory, Data Lake, Synapse, and Databricks. These solutions will enable advanced analytics, reporting, and data-driven decision-making across the organization. By collaborating with product owners, architects, and business stakeholders, you will play a key role in maximizing the value of data and driving measurable commercial impact worldwide.

Design, build, and maintain scalable, efficient, and reusable data pipelines and products on the Azure PaaS data platform.

Collaborate with product owners, architects, and business stakeholders to translate requirements into technical designs and data models.

Enable advanced analytics, reporting, and other data-driven use cases that support commercial initiatives and operational efficiencies.

Ingest, transform, and optimize large, complex data sets while ensuring data quality, reliability, and performance.

Apply DevOps practices, CI/CD pipelines, and coding best practices to ensure robust, production-ready solutions.

Monitor and own the stability of delivered data products, ensuring continuous improvements and measurable business benefits.

Promote a “build-once, consume-many” approach to maximize reuse and value creation across business verticals.

Contribute to a culture of innovation by following best practices while exploring new ways to push the boundaries of data engineering.

5+ years of experience as a Data Engineer with proven expertise in Azure Synapse Analytics and SQL Server.

Advanced proficiency in SQL, covering relational databases, data warehousing, dimensional modeling, and cubes.

Practical experience with Azure Data Factory, Databricks, and PySpark.

Track record of designing, building, and delivering production-ready data products at enterprise scale.

Strong analytical skills and ability to translate business requirements into technical solutions.

Excellent communication skills in English, with the ability to adapt technical details for different audiences.

Experience working in Agile/Scrum teams.

Nice-to-Have Skills

• Familiarity with infrastructure tools such as Kubernetes and Helm.
• Experience with Kafka.
• Experience with DevOps and CI/CD pipelines.

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