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Data Engineer
This job description is written in English, the working language for this role.
About the role
As a Data Engineer, you will be responsible for building and maintaining scalable data infrastructure that supports data processing, integration, and analytics across the organization. You will collaborate with Data Scientists, Data Analysts, and technical teams to ensure that data from multiple sources is accurately collected, transformed, and delivered. This role requires strong expertise in SQL, Python, ETL/ELT processes, database technologies, and data pipeline orchestration, with a focus on reliability, performance, and data quality.
What you’ll do
- Design, develop, and maintain scalable ETL/ELT data pipelines to extract, transform, and integrate data from multiple internal and external sources.
- Develop and optimize data integration processes between databases, applications, APIs, and data warehouse environments to support analytical requirements.
- Implement automated data processing workflows using Python, SQL, Apache Airflow, or other orchestration tools to improve data pipeline efficiency and reliability.
- Monitor data pipeline execution, identify processing failures and performance bottlenecks, and perform troubleshooting to ensure data availability in accordance with established Service Level Agreements (SLAs).
- Maintain technical documentation covering data pipeline architecture, data mapping, transformation rules, integration workflows, and operational procedures.
- Collaborate with Data Scientists, Data Analysts, and business stakeholders to understand data requirements and provide suitable data structures and integration solutions.
What you’ll bring
- Bachelor's degree in Computer Science, Information Technology, Information Systems, Data Engineering, Software Engineering, or a related field.
- Minimum 3+ years of experience as a Data Engineer, ETL Developer, Database Developer, or a related data engineering role.
- Strong proficiency in SQL and Python for data extraction, transformation, integration, and processing automation.
- Hands-on experience designing, developing, and maintaining ETL/ELT pipelines using tools such as Apache Airflow, Apache NiFi, SSIS, or equivalent technologies.
- Experience integrating data from REST APIs, databases, flat files, and other structured or semi-structured data sources.
- Familiarity with cloud-based data platforms such as AWS Glue, Azure Data Factory, Google BigQuery, or equivalent services is an advantage.
- Experience integrating data from REST APIs, databases, flat files, and other structured or semi-structured data sources.
Skills
Python ProgrammingSQLApache AirflowApache NiFi