Senior Data Architect

We are currently seeking a Data Architect who can stand up enterprise data platforms to deliver novel, decision-ready information for high-profile clients. The RS21 Data Engineering division consists of data engineers and data architects who are dedicated to developing best-in-class data platforms to help solve some of today’s most challenging business problems. They work collaboratively with the other RS21 functional divisions to develop high performing, cutting-edge data solutions to help business stakeholders make critical decisions based on trustworthy data, presented in a way to highlight meaningful insights.

We’re looking for a Data Architect who’s excited to spearhead the delivery of elegant, big data platforms, and to do so by providing exceptional leadership to a team of Data Engineers, Analysts and QA.  We're creating world class systems to make our world a better place, and these systems require world class skills. 

This is a full-time position reporting to the Chief Solutions Architect.  

Responsibilities:

• Develops and oversees development of production-quality data platforms.
• Designs and develops data integration strategies to ensure the right data into the data solutions to support the data analytics use cases.
• Mentors a team of data engineers to build the skills required to work effectively with business stakeholders to derive functional and technical requirements from business objectives and needs.
• Identifies best practices regarding data collection, storage, integration, warehousing, and lifecycle management. Develops standards and procedures to ensure those best practices are known and implemented consistently.
• Conceptualize, design, model and deploy data models (conceptual, logical, and physical) to specifically address client business needs.
• Meets with prospective customers and contributes to proposal development, initial project planning, and project cost estimation.

Qualifications:

• Bachelor’s degree with 10+ years of experience developing modern data platforms from conception to post-deployment.
• Ability to obtain Public Trust
• Experience with modern data warehousing solutions: Redshift, Snowflake, Databricks
• Experience in building cloud-native data platforms on AWS, leveraging services like S3, Redshift, Lambda,  Athena, and others for scalable data solutions.
• Expert level experience with Python and SQL
• Experience with distributed frameworks (Spark, Trino, Flink)
• Experience designing, developing, and managing modern data platforms such as data warehouses, data lakes and/or data lakehouses.
• Experience with distributed streaming frameworks (Flink, Spark Structured Streaming, Kafka)
• Excellent leadership skills, written and verbal communication skills, and experience interfacing with prospective or existing business stakeholders.
• Demonstrated ability to accept strategic guidance from leadership and transform that guidance into an actionable plan with a clear path of execution.
• Experience mentoring technical teams.
• Experience managing an enterprise-level data solution through the entire software lifecycle.
• Experience gathering requirements, deriving functional and technical specifications, and defining and prioritizing the necessary tasks needed to fulfill those requirement and specifications according to the project’s period of performance (PoP).
• Experience defining and implementing data governance rules to address business needs, regulatory requirements, and data sensitivity.
• Demonstrated understanding of data security best practices and experience integrating data security safeguards to prevent accidental and/or intentional privacy breaches and data misuse.

 Nice to Have:

• Bachelor’s degree in computer science or similar field.
• Experience working with state, local, and federal agencies.
• Experience using NoSQL databases in production systems.
• Familiarity with languages such as Java, Scala, Go, or Rust, especially in cloud-native or distributed data environments.
• Experience working with open table formats such as Iceberg, Delta, Hudi.
• Data mapping between source systems, data warehouses, and data marts.
• Prior experience implementing business rules via stored procedures, middleware, or other technologies.
• Familiarity with developing and implementing data extraction procedures from other systems.
• Develop or maintain standards, such as organization, structure, or nomenclature, for the design of data warehouse elements, such as data architectures, models, tools, and databases.
• Create supporting documentation, such as metadata and diagrams of entity relationships, business processes, and process flow.
• Create plans, test files, and scripts for data warehouse testing, ranging from unit to integration testing.