Halian | Managed Services, Recruitment Agency & Contract Staffing
Linkedin · Posted yesterday
Data Engineer (m/f/d)
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Indexed description
Role OverviewWe are seeking a skilled Data Engineer to design, build, and maintain scalable data pipelines and infrastructure. This role focuses on enabling reliable data access, improving data quality, and supporting analytics, reporting, and AI/ML initiatives. The ideal candidate is passionate about working with large datasets and modern data platforms.
Key Responsibilities
- Design, build, and maintain scalable data pipelines and ETL/ELT processes.
- Develop and manage data architectures, including data lakes, warehouses, and data marts.
- Ensure data quality, integrity, and consistency across systems.
- Collaborate with data scientists, AI engineers, analysts, and business stakeholders.
- Optimize data pipelines and workflows for performance and cost-efficiency.
- Implement data governance, security, and compliance best practices.
- Monitor data systems, troubleshoot issues, and ensure high availability.
- Integrate data from multiple sources including APIs, databases, and streaming platforms.
- Maintain documentation for data pipelines, systems, and processes.
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field.
- 5+ years of experience in data engineering or a related role.
- Strong programming skills in Python, Java, or Scala.
- Proficiency in SQL and working with relational and non-relational databases.
- Experience with big data technologies such as Apache Spark, Hadoop, or similar.
- Hands-on experience with ETL/ELT tools and orchestration frameworks (e.g., Airflow).
- Familiarity with cloud platforms such as Azure, AWS, or Google Cloud.
- Strong understanding of data modeling and database design principles.
- Basic knowledge of AI engineering concepts and ML workflows.
- Highly preferred: Experience working with Databricks.
- Experience with data warehousing solutions (e.g., Snowflake, BigQuery, Redshift, Azure Synapse).
- Knowledge of streaming technologies (e.g., Kafka, Kinesis).
- Experience with containerization and orchestration tools (Docker, Kubernetes).
- Exposure to CI/CD pipelines and DevOps practices.
- Familiarity with supporting ML/AI use cases (feature engineering, data pipelines for models).
- Strong problem-solving and analytical thinking
- Attention to detail and data accuracy
- Effective communication and collaboration skills
- Ability to work in a fast-paced, data-driven environment
- Continuous learning mindset
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