Data Engineer I (R-19886)

Shape the Future with Dun & Bradstreet At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate. Since 1841, businesses have trusted us to turn uncertainty into opportunity. We’re a diverse, global team that values creativity, collaboration, and bold ideas. Are you ready to make an impact and help shape what’s next? Join us! Explore opportunities at dnb.com/careers.

Key Responsibilities: Coding & Development - Write, review, test, and maintain code, including SQL and Python, to build data tools, automations, and ingestion and transformation workflows that support Research and Managed Services - Automate manual processes and develop data tools to improve efficiency, accuracy, quality, and throughput - Develop and promote coding standards and contribute to code reviews within the agile team - Build and maintain web-scraping solutions, API integrations, and reusable data-processing components - Support scalable ETL/ELT pipelines for structured and unstructured data Source Evaluation & AI Enablement - Identify prospective sources that can feed AI solutions and Research and Managed Services workflows - Define and apply source-evaluation criteria covering relevance, authority, freshness, completeness, coverage, consistency, accessibility, legal or licensing constraints, privacy, security, and technical compatibility - Perform source profiling, sample validation, proof-of-concept testing, and comparative assessments before recommending onboarding - Document source decisions, metadata, lineage, ownership, limitations, refresh expectations, and approved use cases - Implement and support AI-enabled workflows using LangChain or equivalent orchestration frameworks, large language models, embeddings, retrieval-augmented generation, vector databases, and prompt-engineering approaches where applicable - Monitor source and AI-workflow performance and recommend remediation, replacement, or additional sources when quality or coverage falls below requirements Operational Tasks - Perform day-to-day operational activities supporting Research and Managed Services, including monitoring, exception handling, data maintenance, and issue resolution - Perform database administration activities, including performance tuning and implementation of best practices - Implement new data-maintenance processes and provide end-to-end process ownership - Ensure data integrity by validating, reconciling, and regularly cleaning data - Investigate and resolve production incidents, pipeline failures, data-quality issues, and operational exceptions - Follow applicable data governance, security, and operational standards Collaboration & Continuous Learning - Evaluate and implement new technology solutions, and proactively learn and adopt new tools, platforms, and methodologies introduced by the organization - Communicate with stakeholders and conduct knowledge-exchange sessions for technical and non-technical audiences - Develop and maintain data documentation, including data dictionaries, source assessments, data-flow diagrams, data mappings, runbooks, and data lineage - Collaborate with cross-functional teams across Data & Analytics, Technology, Research Services, Managed Services, Product, and Data Governance - Additional duties as assigned.

Key Skills: - Strong SQL and Python skills, with demonstrated ability to write and maintain code as a core part of daily work - Experience with Playwright, Selenium, and other web-data collection techniques - Experience developing and supporting data-ingestion, transformation, and ETL/ELT workflows - Ability to collect and interpret data from multiple sources, including web scraping and GCS/S3, and formats including delimited files, XML, JSON, and PDF - Working knowledge of data systems and databases used to maintain data pipelines - Experience with Power BI, Tableau, or other dashboard tools - Experience managing stakeholders and project plans - Proficiency in Microsoft Office Suite - Willingness and demonstrated ability to learn new technologies as they are introduced - BigQuery experience and knowledge of AWS and/or GCP - Hands-on experience implementing AI solutions using LangChain or an equivalent orchestration framework - Exposure large language models, prompt engineering, retrieval-augmented generation, embeddings, vector databases, AI agents, or graph databases - Knowledge of Data Operations methodologies, data management approaches, ServiceNow, and/or Jira - Experience with NoSQL technologies, SQL Server administration, R programming, web technologies, and data mapping from multiple sources.

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