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Well-known employer, remote/hybrid option, mid-level generalist data role, and metro location increase applicant competition.
Core data engineering skills (Python, SQL, Airflow, cloud) are highly transferable across industries.
Explicit years plus required Python, SQL, Airflow and cloud experience create strict shortlisting filters.
Develop, maintain, and enhance scalable, reliable data pipelines and backend systems using Python, SQL, and Airflow.
Work with large-scale customer and behavioural datasets to support analytics, machine learning, personalisation, recommendations, and product insights.
Collaborate with cross-functional teams to deliver data solutions and troubleshoot production issues ensuring operational stability.
2-4 years of experience in backend, data engineering, or platform engineering roles.
Strong programming skills in Python with clean, maintainable, and well-tested code practices.
Proficient in SQL and experience with data pipelines (design, develop, maintain).
Experience with Airflow or similar workflow orchestration; familiarity with at least one cloud platform (AWS, Azure, or GCP).
Experienced working with large-scale data environments supporting analytics and machine learning use cases.
Proficient in building reliable and maintainable backend data systems with a focus on data quality and operational stability.
Comfortable in collaborative, fast-paced teams interfacing with product and analytics stakeholders, contributing to continuous improvement.