Senior Data Management Professional - Automation Engineer - Economics News

Bloomberg•Princeton, NJ

1d•$110,000 - $190,000

About The Position

Bloomberg’s Economics Data team supports high-impact, time-sensitive headline data publishing across Bloomberg News and Bloomberg Terminal. The team manages automated headline generation and economic data release workflows using sources such as government agencies, central banks, national statistics offices, vendor feeds, news APIs, web sources, email, and social media. These workflows support economic indicators, automated news headlines, and downstream data delivery. The Senior Data Management Professional – Economics News Automation will manage, coordinate, and improve automated headline and economic data workflows across acquisition, extraction, validation, monitoring, publishing, and remediation. The role focuses on modernizing and scaling automation, reducing operational risk, improving data quality and timeliness, and strengthening end-to-end visibility. The successful candidate will work with News, Engineering, and Product teams to ensure automated outputs are accurate, timely, reliable, observable, and fit for purpose, while applying data product ownership, technical fluency, workflow design, stakeholder coordination, and quality management.

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.
Proven 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, with 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 across 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 on automation-first product management, workflow design, data quality, operational excellence, and scalable automation practices.