Data Architect Lead

Job Summary

Lead the development and execution of the organization’s data architecture strategy, overseeing the design of scalable and secure data platforms. Provide technical leadership on data modeling, integration, governance, and infrastructure while managing a team and collaborating with stakeholders on data initiatives.

Responsibilities

• Develop and maintain the enterprise data architecture strategy, standards, and roadmap aligned with business goals.
• Design scalable conceptual, logical, and physical data models for OLTP, OLAP, and data lake/lakehouse environments.
• Architect data pipelines, ETL/ELT processes, and integration across source systems, data warehouses, and applications.
• Select suitable data platforms, tools, and technologies including cloud data warehouses and streaming platforms.
• Define and enforce frameworks for data governance, quality, master data management, and metadata management.
• Lead and mentor data architects, engineers, and analysts, reviewing and approving technical designs.
• Set technical direction on data security, privacy, access control, and compliance such as GDPR and data residency.
• Collaborate with business and technical teams to translate requirements into data architecture solutions and support data migration and integration projects.

Requirements

• 8-10 years of experience in data architecture or related roles, with 3-5 years in a lead or architect role.
• Proficient in designing data models including dimensional, star/snowflake schemas, and normalized/denormalized models.
• Expertise in at least one major cloud data platform such as AWS Redshift/Glue, Azure Synapse/Data Factory, GCP BigQuery/Dataflow, Snowflake, or Databricks.
• Strong SQL skills and experience with ETL/ELT tools like Informatica, Talend, dbt, or Azure Data Factory.
• Experience with data warehousing, data lakes, and lakehouse architectures.
• Knowledge of data governance, master data management, data quality, and metadata management principles.
• Experience with API-based and event-driven integration technologies such as Kafka, REST, or OIC.
• Ability to manage stakeholders and translate business needs into technical architecture.
• Experience leading and mentoring technical teams is desirable.
• Familiarity with BI/reporting tools, AI/ML data pipeline requirements, data security/compliance frameworks, relevant certifications, industry-specific experience, and programming in Python or Scala are additional pluses.

We refresh listings regularly, but some roles close early on the source platform.