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.
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