Data Engineer

Quick Facts

• Role: Data Engineer

Description

The Data Engineer designs, builds, and maintains an enterprise data lake/lakehouse platform supporting analytics, data distribution, and AI/ML initiatives. The role includes developing scalable data pipelines, ensuring high-quality and secure data flows, and enabling trusted data for operational, analytical, and AI/ML use cases.

Responsibilities

• Contribute to the development of the enterprise data lake/lakehouse using Databricks and Snowflake

• Build and maintain batch and streaming data integration pipelines across internal systems, external partners, and cloud services

• Implement ETL/ELT and reverse ETL processes for analytics, reporting, and AI/ML workloads

• Develop, optimize, and maintain scalable pipelines for structured, semi-structured, and unstructured data

• Monitor, troubleshoot, support, and resolve data pipeline and data availability issues

• Automate ingestion, transformation, and distribution workflows with orchestration tools

• Create and maintain metadata catalogs, data lineage, and feature stores

• Collaborate with data scientists, analysts, and business stakeholders to deliver data solutions

• Evaluate and adopt new tools/technologies to improve platform performance, cost management, and engineering practices

• Follow best-in-class development, testing, and documentation standards, including CI/CD

• Apply and maintain data quality rules for accuracy, completeness, and consistency across pipelines

Requirements

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or equivalent technical field

• 3+ years of hands-on experience in data engineering or a similar role

• Very good knowledge of English (written and spoken)

• Strong experience with data processing frameworks: Apache Spark, Snowflake, or Databricks

• Strong experience with data storage technologies such as Lakehouse/Delta Lake and data lakes

• Strong experience with Python and SQL

• Solid understanding of data modeling, ETL/ELT, and data warehousing principles

• Experience with orchestration tools (e.g., Airflow, Prefect)

• Familiarity with cloud platforms (preferably Azure)

• Experience with metadata management tools

• Strong analytical and problem-solving skills

• Ability to work collaboratively in cross-functional teams

Benefits

• Contract of employment (long-term cooperation)

• Annual reward

• Flexible working hours and hybrid work model

• Diverse and inclusive workplace

• Festive benefits paid in April and December

• Medical care with basic dental package (Medicover), with possibility to extend to Damian Medical Center

• Possibility to extend medical care to family members

• Life insurance with possible extended scope

• Sports card (Medicover)

• Language courses

• Extensive training offer

• Wellbeing activities and CSR, with space for your initiatives

• Discounts for meals and special offers at Platan Business Park