Position Summary: KleisTech is looking for experienced DBT Data Engineers who are passionate about data and eager to help tackle our clients’ analytics challenges. As a DBT Data Engineer, you will be responsible for building and maintaining data pipelines, developing DBT models, and ensuring the seamless integration of data for analytics purposes. This role requires a deep understanding of cloud technologies, data architecture, and ETL processes.
Key Responsibilities:
- Documentation & Lineage: Generate comprehensive documentation around model descriptions, dependencies, SQL, sources, and tests. Create lineage graphs to provide transparency into data processes and business logic mapping.
- External Data Integration: Work with external client data to build and optimize DBT solutions for real-time data collection and processing.
- Pipeline Design & Development: Involve in the design of data pipelines and develop DBT models to transform raw data into actionable insights.
- Data Modeling: Create models, identify patterns, and ensure data pipeline architectures are robust, scalable, and secure.
- Collaboration: Work closely with management to align data strategies with company objectives and support business needs.
- Validation & Compliance: Develop new data validation methods and tools, ensuring compliance with data governance and security policies.
- Data Transformation: Design and implement data models and transformations using DBT, tailored to meet specific business requirements.
- Technical Expertise: Leverage your experience in ETL tools, cloud data warehouses (especially Snowflake), and cloud technologies (AWS, Azure, Google Cloud) to optimize data processes.
Essential Skills:
- DBT & Snowflake Expertise: 2+ years of hands-on experience with DBT and Snowflake ETL processes, including model development, package maintenance, and documentation.
- SQL Proficiency: Strong skills in SQL and database table design, capable of writing efficient queries for large datasets.
- Cloud Technology Experience: Hands-on experience with AWS, Azure, or Google Cloud, including data architecture design and ETL process optimization.
- Programming: Proficiency in Python, Spark, or Scala for data engineering tasks.
- CI/CD & DevOps: Experience with CI/CD and DevOps practices, especially in the context of Snowflake and cloud-based data platforms.
Desirable Skills:
- ETL Testing: Familiarity with ETL testing and data orchestration tools.
- Pharmaceuticals Sector Experience: Previous experience working within the Pharmaceuticals sector is an advantage.
- Certifications: Certification in DBT Tool, Snowflake, or other related data engineering technologies is highly desirable.
Qualifications:
- Education: Degree in Computer Science, Software Engineering, or a related field.
Qualities:
- Problem-Solving: Demonstrates confidence, strong decision-making skills, and a logical approach to problem-solving.
- Independence: Capable of independently tackling problems and following up with developers on related issues.
- Team Collaboration: Able to work in a self-organized, cross-functional team and iterate based on feedback.
- Client Interaction: Comfortable working seamlessly with clients across multiple geographies.
- Analytical Skills: Strong analytical, presentation, reporting, documentation, and interactive skills.
Join KleisTech as a DBT Data Engineer. We’re hiring experienced professionals for remote roles focused on building and optimizing data pipelines using DBT and Snowflake. Apply now to advance your career in data engineering.