Middle Data Engineer

N-iX · Ukraine

  • Junior
  • Full-time
  • Posted 2026-09-16
  • Confirmed live on 25 September 2026

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Job description

Responsibilities:

• Build, maintain, and optimise scalable ETL/ELT pipelines (batch and near-real-time) on Azure Data Cloud Platform (e.g., Data Lake, Microsoft Fabric, Azure Data Factory).

• Develop and refine data models to support BI reporting, analytics, and ML/AI use cases.

• Write efficient, well-documented T-SQL and PySpark code following team coding standards.

• Implement automated testing, data validation, and monitoring (SLAs, alerts) to ensure pipeline reliability.

• Contribute to data governance practices, including lineage tracking, metadata management, and quality controls.

• Support CI/CD pipelines for data assets, ensuring version control and reproducibility.

• Partner with analytics engineers to scope, refine, and prioritise data requirements from business stakeholders.

• Work with Analysts, BI Developers, Data Scientists, and business teams to translate requirements into production-ready data solutions.

• Provide input on data readiness for machine learning and analytics projects.

• Contribute to the evolution of the ED&I data platform, including tooling, standards, and documentation.

• Stay current with emerging data engineering patterns and technologies; propose improvements to team processes.

• Leverage AI-driven development tools (e.g., generative-AI code assistants, automated data profiling) to accelerate delivery.

• Support performance tuning and cost optimisation across the data platform.

Requirements:

• 3+ years in data engineering or a closely related role.

• Bachelor’s degree in Computer Science, Data Engineering, or a related field.

• Strong T-SQL skills and working proficiency in PySpark or Python for data processing.

• Hands-on experience with MS Azure Storage Explorer and SSMS.

• Hands-on experience with cloud-based data engineering services and orchestration tools (e.g., Azure Data Factory, Microsoft Fabric).

• Practical experience building ETL/ELT pipelines and dimensional or analytical data models.

• Familiarity with CI/CD practices in data engineering, including version control (Git) and automated testing.

Nice to have:

• Experience with real-time or streaming data architectures.

• Experience with PowerShell, Apache Kafka, and/or KQL.

• Exposure to AI/ML workflows (feature engineering, data preparation for model training).

• Familiarity with Power BI or other BI/visualisation tools.

• Experience using AI productivity tools (e.g., ChatGPT, Claude, Copilot, Cursor) in day-to-day and data engineering tasks.

• Understanding of data security, privacy, and compliance considerations.

We offer*:

• Flexible working format - remote, office-based or flexible

• A competitive salary and good compensation package

• Personalized career growth

• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)

• Active tech communities with regular knowledge sharing

• Education reimbursement

• Memorable anniversary presents

• Corporate events and team buildings

• Other location-specific benefits

*not applicable for freelancers

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