Principal Engineer - Data Solutions Architect
Job Overview
Company Overview
Arcesium is a global financial technology firm that solves complex data-driven challenges faced by some of the world’s most sophisticated financial institutions. We constantly innovate our platform and capabilities to meet tomorrow’s challenges, anticipate the risks our clients encounter, and design advanced solutions to help our clients achieve transformational business outcomes.
Financial technology is a high-growth industry as change and innovation continue to disrupt the status-quo and prompt major transformation. Arcesium is at a particularly interesting time in our own growth as we look to leverage our successfully established market position and expand operations in pursuit of strategic new business opportunities. We value intellectual curiosity, proactive ownership, and collaboration with colleagues, and we empower you to meaningfully contribute from day one and accelerate your professional development.
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
- Bachelor's 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
Arcesium and its affiliates do not discriminate in employment matters on the basis of race, color, religion, gender, gender identity, pregnancy, national origin, age, military service eligibility, veteran status, sexual orientation, marital status, disability, or any other category protected by law. Note that for us, this is more than just legal boilerplate. We are genuinely committed to these principles, which form an important part of our corporate culture, and are eager to hear from all qualified individuals.