Lead a portfolio of diverse technology projects and a team of developers with deep experience in distributed microservices, and full stack systems to create solutions that help meet regulatory needs for the company.
Locations (2)
McLean, Virginia, United States
Richmond, Virginia, United States
Compensation
McLean, VA: $197,300 - $225,100 for Full-stack Engineer 4
Richmond, VA: $179,400 - $204,700 for Full-stack Engineer 4
Responsibilities
Lead a portfolio of diverse technology projects and a team of developers with deep experience in distributed microservices, and full stack systems to create solutions that help meet regulatory needs for the company
Share passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, mentoring other members of the engineering community
Collaborate with digital product managers, and deliver robust cloud-based solutions that drive powerful experiences to help millions of Americans achieve financial empowerment
Provide technical leadership and direction across Agile teams, setting standards for design, development, and operational excellence
Partner with architects to define service boundaries, integration patterns, and reusable frameworks
Requirements
Bachelor's Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
Lead the design and development of scalable, enterprise-grade data platforms, with a strong specialization in Databricks and modern cloud technologies, driving complex, cross-functional data initiatives.
Responsibilities
Own and drive the technical architecture of complex, cross-functional data initiatives, covering ingestion, transformation, storage, and serving layers.
Design, develop, and maintain scalable, high-performance data pipelines and distributed data platforms using Databricks and cloud-native technologies across Azure, AWS, or GCP.
Lead enterprise Master Data Management (MDM) initiatives, including golden records, entity resolution, match-and-merge processes, data domains, reference data, hierarchies, and data stewardship.
Architect and integrate agentic AI and LLM-powered solutions, including autonomous agents, RAG pipelines, AI copilots, and orchestration frameworks, into enterprise data platforms.
Build and maintain data foundations for machine learning and AI applications, including feature stores, vector databases, embeddings, and ML/LLMOps pipelines.
Requirements
Bachelor's degree in Computer Science, Engineering, Management Information Systems, or a related discipline
Lead the design and development of scalable, enterprise-grade data platforms, with a strong specialization in Databricks and modern cloud technologies, driving complex, cross-functional data initiatives.
Responsibilities
Own and drive the technical architecture of complex, cross-functional data initiatives, covering ingestion, transformation, storage, and serving layers.
Design, develop, and maintain scalable, high-performance data pipelines and distributed data platforms using Databricks and cloud-native technologies across Azure, AWS, or GCP.
Lead enterprise Master Data Management (MDM) initiatives, including golden records, entity resolution, match-and-merge processes, data domains, reference data, hierarchies, and data stewardship.
Architect and integrate agentic AI and LLM-powered solutions, including autonomous agents, RAG pipelines, AI copilots, and orchestration frameworks, into enterprise data platforms.
Build and maintain data foundations for machine learning and AI applications, including feature stores, vector databases, embeddings, and ML/LLMOps pipelines.
Requirements
Bachelor's degree in Computer Science, Engineering, Management Information Systems, or a related discipline
Lead the design and development of scalable, enterprise-grade data platforms, with a strong specialization in Databricks and modern cloud technologies, driving complex, cross-functional data initiatives.
Responsibilities
Own and drive the technical architecture of complex, cross-functional data initiatives, covering ingestion, transformation, storage, and serving layers.
Design, develop, and maintain scalable, high-performance data pipelines and distributed data platforms using Databricks and cloud-native technologies across Azure, AWS, or GCP.
Lead enterprise Master Data Management (MDM) initiatives, including golden records, entity resolution, match-and-merge processes, data domains, reference data, hierarchies, and data stewardship.
Architect and integrate agentic AI and LLM-powered solutions, including autonomous agents, RAG pipelines, AI copilots, and orchestration frameworks, into enterprise data platforms.
Build and maintain data foundations for machine learning and AI applications, including feature stores, vector databases, embeddings, and ML/LLMOps pipelines.
Requirements
Bachelor's degree in Computer Science, Engineering, Management Information Systems, or a related discipline
Help develop and strengthen the backend infrastructure of an inclusive, mobile-first digital platform, taking ownership of complex technical challenges, investigating and resolving backend issues while improving system performance, scalability, and reliability.
Responsibilities
Design, develop, and deploy scalable, resilient backend services using cloud-first architectures, NoSQL databases, and event-driven technologies.
Investigate complex backend issues, lead technical troubleshooting, identify root causes, and define clear paths toward resolution.
Optimize system performance, reliability, availability, and data integrity as the platform scales.
Build and maintain well-structured, self-documented APIs using NestJS, GraphQL, and REST.
Develop and maintain real-time application features using WebSockets.
Help develop and strengthen the backend infrastructure of an inclusive, mobile-first digital platform, taking ownership of complex technical challenges while improving system performance, scalability, and reliability.
Responsibilities
Design, develop, and deploy scalable, resilient backend services using cloud-first architectures, NoSQL databases, and event-driven technologies.
Investigate complex backend issues, lead technical troubleshooting, identify root causes, and define clear paths toward resolution.
Optimize system performance, reliability, availability, and data integrity as the platform scales.
Build and maintain well-structured, self-documented APIs using NestJS, GraphQL, and REST.
Develop and maintain real-time application features using WebSockets.
Help develop and strengthen the backend infrastructure of an inclusive, mobile-first digital platform, taking ownership of complex technical challenges, improving system performance, scalability, and reliability.
Responsibilities
Design, develop, and deploy scalable, resilient backend services using cloud-first architectures, NoSQL databases, and event-driven technologies
Investigate complex backend issues, lead technical troubleshooting, identify root causes, and define clear paths toward resolution
Optimize system performance, reliability, availability, and data integrity as the platform scales
Build and maintain well-structured, self-documented APIs using NestJS, GraphQL, and REST
Develop and maintain real-time application features using WebSockets
Help develop and strengthen the backend infrastructure of an inclusive, mobile-first digital platform, taking ownership of complex technical challenges, improving system performance, scalability, and reliability.
Responsibilities
Design, develop, and deploy scalable, resilient backend services using cloud-first architectures, NoSQL databases, and event-driven technologies.
Investigate complex backend issues, lead technical troubleshooting, identify root causes, and define clear paths toward resolution.
Optimize system performance, reliability, availability, and data integrity as the platform scales.
Build and maintain well-structured, self-documented APIs using NestJS, GraphQL, and REST.
Develop and maintain real-time application features using WebSockets.
Own the operations, security, and cost of the data platform, migrating from BigQuery to Snowflake, and extending practices to Postgres and NoSQL databases.
Responsibilities
Own administration and day-to-day operations of Snowflake, including environments, warehouses, performance, and the operational side of the migration from BigQuery
Define consistent operating practices for data ingestion from S3 and vendor files, structured and semi-structured data, and ML and AI workloads, using infrastructure as code and CI/CD for data
Extend consistent operational practices to the Postgres and NoSQL databases used by application teams, including backups, performance, and access
Apply least-privilege permissions, design appropriate data access roles, and integrate data tools with SSO, with encryption and auditing for sensitive data
Manage the external vendors and tools used by the data team, covering access, SSO integration, configuration, and licensing
Requirements
Nice to have: Snowflake migration
Nice to have: BigQuery
Nice to have: Snowflake certifications
Nice to have: Machine learning and AI workloads support
Staff Data Engineer (Databricks specialist)NewJobgether · Remote, Germany
Senior DataOps Engineer, Data PlatformNewTopDog Law · Remote, India