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Mid-level generalist data role in a metro with a known brand and broad skill requirements increases competition.
Core data engineering skills like Python, SQL and cloud are highly transferable across industries.
Explicit 2-5 year requirement plus mandatory Python, SQL, AWS and Airflow skills enforce strict shortlisting.
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Build and maintain data pipelines supporting scalable analytics and real-time data processing integrated with downstream systems.
Implement and monitor data governance and quality processes ensuring data integrity throughout its lifecycle.
Collaborate across teams for pipeline integration, code review, proactive testing, and code optimization to meet service-level agreements.
Bachelor’s Degree in Computer Science, Data Engineering, Data Science or related field.
2-5 years of experience coding in Python and SQL in production and non-production environments within cloud-based infrastructures (e.g., AWS, EC2).
Experience working with workflow tools like GitLab and Airflow and applying software development life cycle best practices.
Work Experience Required: 2-5 years in relevant data engineering roles.
Experienced in designing and optimizing data pipelines within cloud environments, emphasizing production readiness and maintainability.
Familiar with monitoring, testing, and code review processes to ensure high data quality and operational stability.
Comfortable analyzing problems and recommending technical solutions informed by previous coding and system integration experience.