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High competition due to popular mid-level data role, metro locations, and broad generalist skill requirements.
Medium sensitivity: core data engineering skills are transferable but domain-specific pipelines and cloud experience matter.
Medium strictness: requires proven data engineering experience and core skills (Python, SQL, ETL), but no explicit years.
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Build and prototype scalable data pipelines and new API integrations handling increasing data volume and complexity.
Write reusable, testable Python code for data ingestion and integration tasks, employing SQL for data insights in collaboration with business stakeholders.
Maintain and improve engineering infrastructure ensuring solutions meet functional, performance, scalability, and reliability requirements with end-to-end responsibility including development, QA, and dev-ops roles.
Proven experience as a Data Engineer or similar role focused on data integration and management.
Strong programming skills in Python including API interactions and automation.
Solid foundation in SQL and relational database design.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in handling multiple projects in a fast-paced environment with ability to adapt to changing priorities.
Capable of collaborating directly with business analysts and data scientists to support use cases and translate requirements.
Familiarity or understanding of cloud infrastructure design and implementation for scalable data solutions.