Principal Engineer - Data Solutions Architect

Arcesium seeks an exceptional Senior Solutions Architect to join our Corporate Technology team. This candidate should have a strong background in database design, architecture, and data governance. In this role, you will help architects and implement foundational databases and data warehousing solutions.

What you ll do

• Design and architect scalable, cloud-native data solutions within the Aquata platform.
• Build and maintain data pipelines for ingesting, validating, and harmonizing data from multiple sources.
• Design and implement backend data services, APIs, and microservices to support platform functionality.
• Develop backend components for data processing, transformation, and distribution layers.
• Design relational and dimensional data models to support enterprise-scale data management.
• Implement data governance frameworks ensuring data quality, lineage, and security across the platform.
• Build and optimize backend data access layers and query optimization services.
• Architect data distribution mechanisms and backend APIs to support downstream consumption and analytics.
• Identify architectural gaps, data quality issues, and performance bottlenecks; recommend and implement solutions.
• Provide technical leadership and mentorship on data architecture and backend development best practices.
• Contribute to the evolution of Data Warehouse platform capabilities, backend services, and technical roadmap.

What you ll need

• Bachelors degree in computer science, Engineering, Information Technology, or related discipline
• 9+ years of experience in data architecture, data warehousing, and enterprise data platform implementation
• Strong programming skills in Python, Java, or Scala for backend development
• Experience building RESTful APIs and microservices architecture.
• Strong expertise in cloud-native data architecture and AWS services (S3, Redshift, Aurora, Glue, Lambda, EC2, API Gateway)
• Deep experience with data ingestion patterns, ETL/ELT processes, and data pipeline orchestration
• Proficiency in data modeling (logical, physical, and dimensional) for analytical workloads
• Hands-on experience writing complex SQL and optimizing query performance.
• Experience building backend data processing engines and transformation services.
• Experience with data quality frameworks, data validation, and reconciliation processes
• Strong understanding of data governance, metadata management, and data lineage
• Knowledge of API design and integration patterns for data distribution
• Experience with modern data stack technologies (e.g., Airflow, dbt, Spark)
• Familiarity with containerization (Docker, Kubernetes) and orchestration
• Understanding of distributed systems and scalable backend architecture patterns
• Initiative-taking learner who quickly adapts to innovative technologies and business domains.

Preferred:

• Experience with financial services data (investment data, accounting, portfolio management)
• Knowledge of data streaming and real-time data processing (Kafka, Kinesis)
• Experience building event-driven architectures and message queue systems.
• Familiarity with AI/ML integration in data platforms
• Experience with data observability and monitoring tools
• Background in building multi-tenant SaaS data platforms
• Understanding of regulatory requirements for financial data management
• Experience with DevOps practices and Infrastructure as Code (Terraform, CloudFormation)
• Knowledge of GraphQL or other advanced API technologies
• Familiarity with caching strategies (Redis, Memcached) for data services