Enterprise Data Architect & Technical Lead
Based in United StatesFull-TimeLead
SalaryApproximately $155,500–$188,200 (depending on experience and location)
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Job Details
- Experience
- 10–15 years
- Required Skills
- SQLErwinMicrosoft SQL ServerOracleSnowflakeData modeling
Requirements
- Bachelor’s degree in Computer Science, Information Systems, Engineering, Business, or related field (or equivalent experience).
- 10–15 years of experience in data architecture, data engineering, or enterprise data platform leadership roles.
- Strong expertise in SQL-based databases (SQL Server, Oracle) and cloud/columnar platforms such as Snowflake or Vertica.
- Hands-on experience with ETL/middleware tools (e.g., Informatica, MuleSoft) and data integration frameworks.
- Deep understanding of data modeling tools (e.g., ERwin, ER/Studio) and enterprise data modeling practices.
- Experience managing large-scale structured and unstructured data environments and data transformation pipelines.
- Strong analytical skills with the ability to define, document, and communicate complex data solutions.
- Proven ability to collaborate across technical and non-technical stakeholders.
- Experience with version control systems (Git, TFS, CVS) and modern data development practices (preferred).
- Prior exposure to SAP modules and/or pharmaceutical or regulated industry environments is a strong advantage.
Responsibilities
- Lead the definition, design, and implementation of enterprise-wide data architecture, including data warehouse, integration, and master data management capabilities.
- Own the architecture and evolution of the Enterprise Data Warehouse (EDW) and associated data products.
- Define and enforce enterprise data standards, data lineage, metadata management, and governance practices.
- Design and optimize logical and dimensional data models to support analytics, reporting, and business intelligence use cases.
- Oversee integration architecture including middleware, ETL pipelines, and data movement frameworks.
- Ensure effective implementation of MDM solutions aligned with operational processes.
- Partner with cross-functional stakeholders to translate business requirements into scalable technical architectures.
- Provide technical leadership for data initiatives, ensuring quality, security, and performance.
- Guide data validation, auditing, and quality assurance efforts using SQL and analytical tools.
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