About This Role
Defining and leading the architecture of scalable, secure, and reliable data products is the core of this role, powering analytics, reporting, and data delivery for clients. The Data Architect will partner with product, engineering, and business stakeholders to design modern cloud data platforms, set technical standards, and ensure data products meet quality, performance, and SLA commitments.
Responsibilities
- Define the end-to-end architecture for data products, including ingestion, transformation, storage, governance, and delivery on cloud data platforms
- Partner with product owners and business stakeholders to translate requirements into data models, technical designs, and delivery roadmaps
- Design and oversee scalable batch and streaming pipelines using Databricks, Spark, and Azure data services
- Design AI-ready data products and platform capabilities that support machine learning and generative AI use cases, including feature engineering, vector search, and retrieval-augmented generation (RAG) pipelines
- Establish standards for data quality, security, access control, lineage, and metadata management across data products
- Lead platform modernization and migration initiatives, ensuring client data delivery meets performance and SLA commitments
- Conduct architecture and design reviews, and drive engineering best practices, automation (including AI-assisted development), and release quality controls
- Mentor data engineers and provide technical guidance to cross-functional and vendor teams
Requirements
- 8+ years of experience in data engineering, data architecture, or software development
- 5+ years of experience designing and building data platforms or data products at enterprise scale
- 4+ years of experience with Databricks, Apache Spark, and Delta Lake or similar lakehouse technologies
- 4+ years of experience with Azure, AWS, or GCP data services
- 4+ years of experience with SQL, Python or Scala, and data modeling (dimensional, relational, and lakehouse)
- 3+ years of experience with data governance, security, and access control practices
- 3+ years of experience with CI/CD pipelines, DevOps practices, and Agile methodologies
- Bachelor’s degree in data science, Computer Science, Engineering, Mathematics or an equivalent combination of education, work, and/or military experience
Nice to have:
- Experience in the financial services industry
- Experience with Unity Catalog, data mesh, or streaming technologies such as Kafka or Spark Structured Streaming
- Experience enabling AI/ML and generative AI solutions on Databricks or similar platforms, such as feature stores, vector databases, or RAG pipelines
