Position Title: Solution Architect City: Washington State: DC Country: US Type: Regular Full-Time # of Openings: 1 Company Name: DOT NHTSA
Overview:
Tantus Technologies, Inc. (Tantus) - recognized by the Washington Post as a Top Workplace - is seeking an Solutions Architect to support a federal client. The Solutions Architect (Senior Data Warehouse Architect) will be responsible for designing and implementing advanced data solutions to support the project's goals and align with the overall enterprise architecture. Specialized expertise in designing, building, and enhancing complex data warehouse solutions that handle large-scale, state-specific datasets from multiple sources is essential.
Tantus Technologies, Inc. (Tantus) - recognized by the Washington Post as a Top Workplace - is seeking an API Developer to support a federal client.
Responsibilities
Work closely with the Federal Solutions Architect and cross-functional teams to design efficient and scalable data warehouse architectures, utilizing modern cloud technologies such as Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure.
Implement best practices in data modeling, ETL (Extract, Transform, Load) processes, and database design, using tools like Apache Airflow, Informatica, Talend, or AWS Glue.
Set technical guidelines for the data warehouse, developing data governance strategies, and ensuring the security, compliance, and performance of data pipelines.
Required knowledge and skills
Proficiency in cloud-based data warehouses and server-less data architectures (e.g., AWS Lambda, Azure Functions) is required.
A Bachelor's degree in Computer Science, Information Technology, or a related field is required.
Specialized expertise in designing, building, and enhancing complex data warehouse solutions that handle large-scale, state-specific datasets from multiple sources is essential.
The ideal candidate will possess strong data analytics, data visualization (e.g., Tableau, Power BI, Looker), and machine learning integration skills, ensuring that data warehouses support reporting, advanced predictive analytics, and AI-driven insights.
Experience with data lakes and data lake house architectures is essential, as well as expertise in both structured and unstructured data storage and retrieval using NoSQL databases like MongoDB and SQL databases like Amazon Redshift, Snowflake, or BigQuery.
Proficiency in cloud-based data warehouses and serverless data architectures (e.g., AWS Lambda, Azure Functions) is required, alongside a strong background in data integration from APIs and streaming data sources using platforms like Apache Kafka, Amazon Kinesis, or Google Pub/Sub.
Familiarity with containerization and orchestration technologies such as Docker and Kubernetes for managing scalable data processing environments is a plus.
Requires a minimum of 6 years of experience in data architecture, with at least 3 years as a Solutions Architect.
Abilities
Excellent problem-solving abilities, strong communication, and a collaborative approach are essential to working effectively within Agile/Scrum teams using tools like Jira and Confluence.
Nice to haves
Certifications in cloud platforms or data engineering (e.g., AWS Certified Data Analytics, Google Cloud Professional Data Engineer) are highly desirable.
Qualifications
Proficiency in cloud-based data warehouses and server-less data architectures (e.g., AWS Lambda, Azure Functions) is required.
A Bachelor's degree in Computer Science, Information Technology, or a related field is required.
Specialized expertise in designing, building, and enhancing complex data warehouse solutions that handle large-scale, state-specific datasets from multiple sources is essential.
The ideal candidate will possess strong data analytics, data visualization (e.g., Tableau, Power BI, Looker), and machine learning integration skills, ensuring that data warehouses support reporting, advanced predictive analytics, and AI-driven insights.
Experience with data lakes and data lake house architectures is essential, as well as expertise in both structured and unstructured data storage and retrieval using NoSQL databases like MongoDB and SQL databases like Amazon Redshift, Snowflake, or BigQuery.
Proficiency in cloud-based data warehouses and serverless data architectures (e.g., AWS Lambda, Azure Functions) is required, alongside a strong background in data integration from APIs and streaming data sources using platforms like Apache Kafka, Amazon Kinesis, or Google Pub/Sub.
Familiarity with containerization and orchestration technologies such as Docker and Kubernetes for managing scalable data processing environments is a plus.
Requires a minimum of 6 years of experience in data architecture, with at least 3 years as a Solutions Architect.
