Principal Data Engineer leading Azure platform designs and implementations for enterprise solutions at UBDS Group. Mentoring teams and driving high engineering standards in hybrid environments.
About the role
- Data Engineer building scalable, high-performance data solutions for Fortune 500 clients at ShyftLabs. Collaborating with cross-functional teams to design and maintain robust data pipelines and systems.
Responsibilities
- Collaborate with cross-functional teams to define requirements and deliver reliable solutions.
- Design, develop, and maintain data pipelines and ETL/ELT processes using Python.
- Build and optimize scalable, high-performance data applications.
- Develop and manage real-time streaming pipelines using Pub/Sub or Apache Beam.
- Participate in code reviews, architecture discussions, and continuous improvement initiatives.
- Monitor, troubleshoot, and optimize production data systems for reliability and performance.
Requirements
- 5+ years of professional experience in software or data engineering using Python.
- Strong understanding of software engineering best practices (testing, version control, CI/CD).
- Proven experience building and optimizing ETL/ELT pipelines and data workflows.
- Proficiency in SQL and database concepts.
- Experience with data processing frameworks (e.g., Pandas).
- Understanding of software design patterns and scalable architecture principles.
- Experience with cloud platforms (GCP preferred).
- Knowledge of CI/CD pipelines and Infrastructure as Code tools.
- Familiarity with containerization (Docker, Kubernetes).
- Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent experience).
- Excellent problem-solving, analytical, and communication skills.
Benefits
- We are proud to offer a competitive salary alongside a strong insurance package.
- extensive learning and development resources.
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