Original listing text, shown exactly as published by the company.
Responsibilities
- Design and build scalable data pipelines using Databricks and Spark to ingest, transform, and unify data from multiple enterprise systems
- Develop and maintain medallion architecture (Bronze, Silver, Gold) data models to create reliable and performant “Golden Record” datasets
- Implement data normalization, mapping, and entity resolution techniques (e.g., fuzzy matching, XREF tables) to unify asset data across disparate systems
- Build data workflows to detect and surface Shadow IT across financial, identity, endpoint, and network signals and integrate results into CMDB systems
- Partner with IT, Security, Finance, Procurement, and GRC teams to define and enforce data standards for critical CMDB attributes (e.g., ownership, approval status, lifecycle)
- Develop and maintain data integrations and APIs to synchronize curated datasets into operational systems such as ServiceNow and Jira Assets
- Monitor, troubleshoot, and improve data quality, reliability, and observability across the data platform
On-call work may be necessary occasionally to help address bugs, outages, or other operational issues, with the goal of maintaining a stable and high-quality experience for our customers.
Requirements
- 9+ years of experience building and maintaining data pipelines and large-scale data platforms
- Strong experience with Databricks, Apache Spark, and SQL for distributed data processing and transformation
- Experience designing data models and architectures such as medallion architecture, data lakes, or lakehouse systems
- Proficiency in Python or similar programming languages for data engineering and ETL development
- Experience integrating data from multiple enterprise systems (e.g., SaaS tools, financial systems, identity systems)
- Strong understanding of data quality, data governance, and entity resolution techniques across heterogeneous datasets
- Excellent collaboration and communication skills, with experience working cross-functionally with technical and non-technical stakeholders
Preferred Qualifications
- Experience working with CMDB systems such as Jira Assets or ServiceNow
- Familiarity with identity, security, or IT asset management systems (e.g., Okta, Jamf, Zscaler)
- Experience implementing cost-optimized data processing strategies in cloud environments
- Exposure to financial data systems (e.g., Oracle, Concur) and spend analytics use cases
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field…
