Principal Data Architect
About The Position
The Big Data Principal Data Architect designs and implements high-performing, scalable big data solutions. The role leads the development of data architecture strategies, ensures data integrity, and optimizes data management processes for performance. It includes developing architecture strategies aligned with business goals; leading big data solutions and data pipeline design and implementation; collaborating with cross-functional teams on requirements and data models; applying data governance and management practices to maintain data quality; optimizing storage, processing, and retrieval of large-scale data; evaluating emerging technologies and tools; guiding and mentoring data engineering teams; and keeping current with industry trends and best practices in big data technologies and architectures. The position is hybrid, with a day shift in the United States. Los Angeles, California-based candidates are not eligible. The approximate annual base compensation range is $165,300 to $235,000; the actual offer depends on factors including experience, knowledge, skills, abilities, location, and internal equity.
Requirements
- Bachelor’s degree in Business Analytics, Computer Science, or Statistics, or a master’s degree in Data Science is listed under qualifications.
- English proficiency at C2 level is required.
- The posting lists required skills including data engineering, cloud computing, Databricks Platform, Agile Methodology, collaboration tools, change management, client relations, and numerous industry and business skills.
Nice To Haves
- Certified Data Management Professional – Riversand.
- Databricks Certified Associate Developer for Apache Spark 3.0 – Databricks Academy.
- Databricks Certified Associate Developer for Apache Spark – Databricks Academy.
- Microsoft Certified: Azure Data Engineer Associate – Microsoft.
- Oracle Database 12c Certified Implementation Specialist – Oracle.
Responsibilities
- Develop and implement data architecture strategies to support business goals.
- Lead the design and implementation of big data solutions and data pipelines.
- Collaborate with cross-functional teams to gather requirements and design data models.
- Ensure data quality and integrity through data governance and data management best practices.
- Optimize data storage, processing, and retrieval performance for large-scale data sets.
- Evaluate and recommend emerging technologies and tools for big data processing and analytics.
- Provide technical guidance and mentorship to data engineering teams.
- Stay current with industry trends and best practices in big data technologies and architectures.
Benefits
- Mentorship and world-class learning opportunities are promoted as career-development offerings.
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What This Job Offers
Job Type
Full-time
Career Level
Principal
