data Architect

• Define and own the enterprise data architecture, data strategy, standards, and technical roadmap.
• Design scalable data platforms, data lakes, data warehouses, and lakehouse architectures.
• Develop conceptual, logical, and physical data models aligned with business and technical requirements.
• Architect modern cloud data solutions using AWS, Azure, or Google Cloud Platform.
• Design and oversee ETL/ELT pipelines and data integration across enterprise applications and data sources.
• Establish data governance, data quality, metadata management, lineage, security, and privacy standards.
• Evaluate and recommend databases and data technologies including Snowflake, Databricks, SQL Server, Oracle, PostgreSQL, and NoSQL platforms.
• Design high-performance and highly available data architectures capable of handling large-scale data workloads.
• Define integration strategies using APIs, event-driven architecture, messaging, and streaming technologies such as Kafka.
• Partner with data engineers, architects, developers, DevOps teams, and business stakeholders to translate requirements into technical solutions.
• Provide technical leadership, architecture reviews, design standards, and mentoring to data engineering teams.
• Drive modernization of legacy data platforms toward cloud-native and modern data architectures.
• Ensure solutions meet enterprise requirements for security, compliance, scalability, performance, and cost optimization.

Required Skills

• 15+ years of experience in data architecture, data engineering, or related technology roles.
• Extensive experience designing enterprise data architecture and data platforms.
• Strong expertise in data modeling, database design, and data warehousing.
• Hands-on experience with cloud data platforms such as Azure, AWS, or Google Cloud Platform.
• Strong knowledge of Snowflake, Databricks, Azure Data Factory, AWS Glue, Redshift, or equivalent technologies.
• Advanced SQL and experience with relational and NoSQL databases.
• Strong experience with ETL/ELT, data integration, and data pipeline architecture.
• Experience with data governance, master data, metadata, data quality, and data lineage.
• Knowledge of Kafka, APIs, event-driven architecture, and real-time data processing.
• Experience with Python, Spark/PySpark, or other modern data engineering technologies.
• Strong understanding of data security, privacy, access control, and regulatory compliance.
• Excellent communication, leadership, architecture documentation, and stakeholder-management skills.

Preferred Qualifications

• Experience with Data Mesh, Data Fabric, or Lakehouse architecture.
• Experience with AI/ML data platforms and Generative AI data architectures.
• Experience implementing enterprise MDM and reference data solutions.
• Experience with Terraform, CI/CD, Docker, and Kubernetes.
• TOGAF or other enterprise architecture certification is a plus.
• Experience working in large-sca