Data Engineer (f/m/d)

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We are looking for a skilled Data Engineer to join our team. The successful candidate will be responsible for designing, developing, and maintaining scalable data pipelines using Apache Airflow or similar orchestration tools.

Responsibilities

• Design, develop, and maintain scalable data pipelines using Apache Airflow or similar orchestration tools for building and scheduling workflows.
• Architect and implement efficient data models (star schema, snowflake schema, normalized/denormalized structures) in Snowflake to support business intelligence and analytics needs.
• Collaborate with analytics and data science teams to translate business requirements into data models and ETL processes.
• Optimize Snowflake data warehouse for performance, cost, and scalability.
• Build and maintain CI/CD workflows using Bitbucket Pipelines for automated deployment and testing of data pipelines and models.
• Leverage AWS services (S3, Lambda, ECS) to support data ingestion, transformation, and storage.
• Implement data quality frameworks, perform data validation, monitoring, and anomaly detection to ensure data accuracy and consistency.
• Monitor data pipeline health and troubleshoot issues to ensure reliability and accuracy.
• Ensure adherence to data governance policies and best practices.

Requirements

• Proven experience as a Data Engineer or similar role, with a strong emphasis on data modeling and warehousing.
• Expertise in designing and implementing data models tailored for analytical workloads in Snowflake.
• Hands-on experience with Apache Airflow or similar tools for building and scheduling data workflows.
• Proficiency with AWS services relevant to data engineering (S3, Lambda, EC2).
• Experience with Bitbucket Pipelines or comparable CI/CD tools.
• Advanced SQL skills and experience in query optimization.
• Proficient in Python or other scripting languages for ETL and data processing.
• Strong understanding of data quality concepts, data validation techniques, and experience implementing data quality checks.
• Solid understanding of data warehousing concepts, including dimensional modeling, normalization/denormalization, slowly changing dimensions (SCD), and fact/dimension tables.
• Familiarity with big data concepts and handling large-scale datasets.
• Strong collaboration and communication skills to work across technical and business teams.

Nice to Have

• Experience with containerization technologies such as Docker
• Familiarity with data governance, security standards, and best practices.

What We Offer

• 30 days of vacation per year
• Hybrid work model with flexible working hours
• Opportunities for professional growth and development
• Attractive salary and benefits package
• Chance to work with a global company and international teams

We are an equal opportunities employer and welcome applications from all qualified candidates. We are committed to creating a diverse and inclusive workplace and encourage applications from underrepresented groups.

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