Data Architect

Responsibilities

• Collaborate with other Engineers and Architects to define the enterprise data architecture roadmap.
• Drive the design and optimization of OLTP and OLAP models for scalability, performance, and maintainability.
• Establish standards for data modeling, storage, and integration across systems.
• Partner with engineering stakeholders in developing a comprehensive data and BI strategy aligned with business objectives.
• Define data governance practices, data access control, compliance, and quality standards.
• Lead proof-of-concepts (POCs) for new data technologies and frameworks.
• Own the architectural review process and guidance to development teams on data-related projects.
• Establish and ensure best patterns and practices for ORM usage (Entity Framework and others) and SQL optimization.
• Evaluate and recommend where AI/ML can enhance data-driven decision-making.
• Stay current with modern data engineering trends, cloud-native architectures, and big data platforms.
• Actively participate and take ownership of Data Architecture artifacts via ADR process.
• Drive AI adoption by introducing and guiding teams in leveraging AI capabilities within the data engineering space.
• Liaison between technology and product teams assisting in translating business requirements into tangible architectures.
• Design data architectures that accurately reflect and support evolving complex product and business processes.
• Lead data architecture initiatives, collaborating with cross-functional teams, from concept through implementation, including governance and quality frameworks.
• Identify opportunities for predictive analytics and advanced modeling.

Requirements

• Bachelor’s degree in Computer Science, Data Science, or relevant professional experience.
• 10+ years of relevant professional experience in architecting Enterprise Data and Business Intelligence solutions.
• Proven experience designing and optimizing large-scale data warehouse implementations for multiple business units, with a deep understanding of polyglot environments.
• Ability to architect scalable, high-performance solutions supporting analytical and operational workloads, including query optimization and index management.
• Expertise in modern data architectures (e.g., Medallion, Data Lakehouse, MDM, DataMesh, Streaming) and dimensional modeling architectural patterns (StarSchema, Snowflake, etc.).
• Proficiency in cloud data platforms (Snowflake, Redshift, BigQuery, Synapse, Databricks) and integration with diverse data sources.
• Deep understanding of visualization and reporting platforms (Tableau, PowerBI, etc.).
• Ability to design conceptual, logical, and physical data models using appropriate database technology (SQL, NoSQL, Graph, etc.).
• Familiarity with ORM technologies such as Entity Framework.
• Skilled in building robust ETL/ELT pipelines ensuring data quality and timeliness (experience with Fivetran, dbt, Rivery is a plus).
• Expertise in data governance frameworks, security, compliance, and stewardship.
• Experience with DataOps, including CI/CD for data workflows, pipeline observability, data quality practices.
• Awareness of emerging AI technologies and their implications for data architecture.
• Interest and ability in mentoring and/or training other team members.
• Experience working cross-functionally and promoting collaborative partnerships.
• Proven ability to communicate effectively to various audiences/levels.
• Experience working in a fully remote team is preferred.

Compensation & Benefits

• Base salary: $170,000 - $200,000 annually.