Senior Data Management Professional – Automation Engineer - Economics News

Bloomberg•New York, NY

1d•$110,000 - $190,000

About The Position

The Senior Data Management Professional – Economics News Automation manages, coordinates, and improves high-impact automated headline and economic data workflows. The role drives automation-first operations across acquisition, extraction, validation, monitoring, publishing, and remediation, helping modernize and scale processes, reduce operational risk, improve data quality and timeliness, and strengthen visibility across critical news and economic data workflows. The position works closely with News, Engineering, and Product teams to ensure automated outputs are accurate, timely, reliable, observable, and fit for purpose. It requires data product ownership, technical fluency, workflow design, stakeholder coordination, quality management, and the ability to work through ambiguity in fast-moving, high-impact publishing environments. The Economics Data team supports time-sensitive headline data publishing across Bloomberg News and Bloomberg Terminal, using automated workflows drawing on government agencies, central banks, statistics offices, vendors, news APIs, web and email sources, and social media.

Requirements

Bachelor's degree or equivalent experience in Computer Science, Engineering, Economics, Statistics, Mathematics, Quantitative Finance, Data Management, Editorial, or a related discipline.
Significant experience in data management, data operations, data engineering, hands-on automation, workflow management, or data quality.
Strong understanding of content and its end-to-end data lifecycle, including acquisition, ingestion, transformation, validation, publishing, monitoring, and operational controls.
Experience designing, managing, and improving automated data workflows, ETL pipelines, monitoring frameworks, and operational processes.
Technical proficiency in Python, SQL, scripting, data analysis, visualization, or similar tools used to automate, monitor, and optimize data workflows.
Ability to translate business, editorial, product, and client requirements into technical solutions while collaborating across Engineering, Product, News, Data, and external partners.
Strong analytical and problem-solving skills, including root-cause analysis, data profiling, trend analysis, KPI/SLA definition, issue management, and continuous process improvement.
Excellent communication, stakeholder management, and prioritization skills, including the ability to navigate ambiguity, manage high-impact incidents, and champion scalable, automation-first solutions.

Nice To Haves

Experience with macroeconomic releases, government statistics, central banks, or other market-moving event coverage.
Familiarity with Bloomberg Terminal, BQL, and Bloomberg News content.
Experience building or managing automated publishing, headline generation, event-driven workflows, source acquisition, extraction, or content automation.
Experience designing dashboards for automation performance, publishing success, extraction accuracy, source latency, data health, or operational risk.
Experience leveraging AI in workflow optimization.
Project management experience with Agile delivery, backlog management, JIRA, or similar tools.
Experience coordinating with external institutions, vendors, source providers, exchanges, government agencies, central banks, or content partners to support reliable data access, delivery, and maintenance.
CDMP certification or progress toward it.

Responsibilities

Manage end-to-end automated news and economic data workflows, including acquisition, extraction, validation, publishing, monitoring, remediation, and scheduled or event-driven delivery.
Prioritize incidents, enhancements, and remediation based on market impact, client value, operational risk, and coverage criticality; lead root-cause analysis and continuous improvement.
Partner with Engineering, Product, and News teams to define automation-first workflows, coverage requirements, and functional and technical specifications for tool modernization, controls, testing, and production readiness.
Define and maintain standards for automation quality, source reliability, extraction accuracy, timeliness, publishing success, operational readiness, and governance.
Design monitoring, alerting, and validation frameworks for end-to-end visibility, anomaly detection, exception handling, and downstream delivery assurance.
Research and onboard news and economic data sources, defining source logic, extraction requirements, publishing rules, fallback strategies, ownership, and lifecycle management.
Apply AI, machine learning, statistical methods, and human-in-the-loop approaches to improve ingestion, validation, monitoring, resilience, and scalable automated publishing.
Influence data modeling, metadata, taxonomy, lineage, governance, documentation, release readiness, and operational support for automated data products.
Mentor colleagues in automation-first product management, workflow design, data quality, operational excellence, and scalable automation practices.