Data and Batch Operations engineer is responsible for managing, monitoring, and optimizing batch and ETL-based data operations to support high-performing, high-availability data platforms. This role partners closely with Data Engineering, Product, and Technology teams to ensure data quality, operational excellence, and scalable data solutionspreferably within a financial services environment.
Qualifications
- Bachelors degree or equivalent experience in Data Operations, ETL, Batch Processing, or related fields, preferably within financial services.
- Experience with commercial workload scheduling tools such as
AutoSys
, BMC ControlM
, or equivalent. - Strong expertise in
AWS
, including Apache Airflow
, supporting cloudbased ETL and realtime data pipelines. - Proven ability to deliver highperforming, highavailability data solutions.
- Excellent verbal and written communication skills, with the ability to collaborate effectively across IT and business teams.
- Handson experience with
ServiceNow
, including Incident, Service Request, Change, Problem, Knowledge Management, and reporting modules. - 7-10 years of working experience is required in these areas.
Responsibilities
- Manage endtoend data operations, including validation of incoming data sources, data integration and compilation, and downstream data distribution.
- Ensure bestinclass data quality and accuracy by defining, building, and tracking data accuracy KPIs to provide insights to Product and Data Engineering teams.
- Establish and maintain
batch and ETL job lineage
, ensuring compliance with governance policies and operational standards. - Partner with Data Engineering to ensure operational controls are properly designed, implemented, and functioning effectively.
- Oversee the integration and execution of all inbound and outbound data processes.
- Identify and implement actionable improvements and optimizations to support increasing data volume, complexity, and business demand.
- Provide handson support for user community training related to data usage, reporting, issue resolution, and production support.
- Monitor, triage, prioritize, and assign Data Operations work intake from ServiceNow, IT Service Desk, IT Demand processes, IT Business Partners, and other data and analytics intake channels.
- Design and implement frameworks and methodologies for deploying and scaling Data Operations solutions.
- Contribute to the vision, strategy, and roadmap for the Data Operations practice, including identifying opportunities for growth, efficiency, and modernization.
- Promote a strong culture of process documentation, data governance, operational discipline, and continuous improvement.
- Develop and integrate operational reports, KPI dashboards, and metrics packages to support technology leadership and decisionmaking.
- Evaluate existing ETL platforms and identify alternative solutions when current hardware or software cannot efficiently support largescale data processing requirements.
