Data Engineer

TL;DR

Data Engineer (Azure/Spark): Designing and developing scalable data platforms and pipelines for complex analytics with an accent on distributed data processing and cloud architecture. Focus on implementing robust ETL/ELT workflows using Python and Apache Spark on the Azure data ecosystem.

Location: Remote, hybrid, or onsite in Bulgaria, Poland, or Romania

Company

A software development company providing diverse technology solutions and consulting services across multiple domains.

What you will do

• Design and develop scalable data platforms and reliable pipelines for analytics.
• Implement data processing workflows using Apache Spark and Databricks.
• Evolve cloud data platforms leveraging Azure Data Factory, Synapse, and Data Lake.
• Model data to support downstream reporting and analytical requirements.
• Monitor and optimize pipeline performance for reliability and scalability.
• Collaborate with cross-functional teams to translate business requirements into technical solutions.

Requirements

• 3+ years of experience in data engineering or building data processing platforms.
• Strong proficiency in SQL and Python for pipeline development.
• Hands-on experience with distributed frameworks like Apache Spark or pySpark.
• Practical experience implementing pipelines in cloud environments, specifically Azure.
• Experience with data modeling, data warehousing, and ETL/ELT design.
• Professional proficiency in English.

Nice to have

• Experience with Databricks.
• Familiarity with Airflow for workflow orchestration.
• Knowledge of modern data lake architectures and formats like Parquet and JSON.

Culture & Benefits

• Flexible work schedule with options for remote work or office presence.
• Access to continuous professional education and growth opportunities.
• Comprehensive health and legal support.
• Active professional community and regular team activities.
• Work across a variety of technologies and business domains.