Associate Professional Analyst - Data Processing; Batch Opera

Qualifications

• Bachelors degree or equivalent experience in data operations, ETL, Batch, etc. preferably in the financial services industry providing high-performing, high-availability solutions.
  • Experience with commercial scheduling tools including AutoSys, BMC Control M, or similar tools.
  • Expertise in AWS including Airflow supporting cloud-based ETL and Real-Time data pipelines and frameworks.
  • Excellent communication skills and the ability to effectively interact across the IT and business organization, working effectively to achieve results.
  • Experience with ServiceNow modules including Incident, Service Request, Change, Problem, Knowledge Management, and reports.

. 5-7 years of experience in the required areas.

Responsibilities

• Responsible for data management (validating incoming data sources, data integration/compilation, distribution).
  • Ensuring best-in-class data quality/accuracy; building/tracking data accuracy KPIs for insights for product/data Eng Teams.
  • Establishing batch/ETL job lineage processes/ensure adherence to policies.
  • Ensuring operational controls are in place/working with the Data Eng.
  • Overseeing the integration of all inbound/outbound data sources.
  • Identifying actionable improvements and optimizations to support growing complexity and demand.
  • Hands-on approach to user community data/report training and problem/resolution management.
  • Monitor, triage, and assign data operations work captured through IT service desk, IT Demand intake, IT Business Partner, and other data and analytics demand intake channels.
  • Creating frameworks and methodologies for deploying Data Ops solutions.
  • Contributing to the vision and strategy for the Data Ops practice, including setting development roadmaps, participating in new business, and identifying growth or efficiency opportunities.
  • Promoting a culture of process documentation, strong data governance and operational efficiencies.
  • Integrate reports, key performance indicators (KPIs), metrics packages and related information for technology team leadership.
  • Identify alternative ETL solutions when it becomes evident that existing hardware/software solutions would not handle a large amount of data.