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Mid-level, metro location and generalist data-ops skillset create moderate applicant competition.
Core data operations skills transfer across industries, though financial services experience is preferred.
Explicit 3–5 years plus mandatory AWS/Airflow, scheduling tools and ServiceNow dictate strict filters.
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Support and maintain enterprise data pipelines, ETL processes, and data operations to ensure data accuracy, reliability, and availability.
Monitor and troubleshoot batch and real-time data workflows using cloud-based tools like AWS and Airflow while managing data quality and operational controls.
Collaborate with Data Engineering and business teams to resolve issues, improve operational efficiency, and contribute to the Data Ops practice strategy and framework development.
3-5 years of experience in data operations, ETL support, cloud-based data platforms, and scheduling tools.
Bachelor’s degree or equivalent experience relevant to data operations or ETL, preferably in financial services.
Experience with commercial scheduling tools such as AutoSys, BMC Control-M, or similar.
Experience with AWS including Airflow and ServiceNow modules (Incident, Service Request, Change, Problem, Knowledge Management).
Candidate has experience supporting high-performing, high-availability ETL and batch data solutions, ideally in financial services environment.
Operates effectively in cross-functional teams interfacing between IT and business with strong communication skills.
Demonstrates hands-on problem solving and proactive identification of improvements in data operations workflows and controls.