Enterprise Data Architect

About Our Client

The organization is a technology consulting and software development company delivering cloud, artificial intelligence, data, and enterprise solutions across the United States. It addresses the challenge of integrating and managing complex data environments by providing scalable and strategic technology solutions to diverse clients.

About the Opportunity

The Enterprise Data Architect is responsible for defining and leading the architecture of the enterprise data platform across ingestion, storage, processing, governance, and consumption layers. This role ensures a coherent and scalable data foundation by setting architectural standards and collaborating with data engineering, analytics, machine learning, and business stakeholders. The position plays a crucial role in shaping data infrastructure to support organizational needs and drive data platform initiatives.

Responsibilities

• Define target-state architecture for enterprise data platform including ingestion, storage, processing, and consumption.
• Establish standards for data modeling, schema evolution, partitioning, file formats, and storage.
• Architect lakehouse, warehouse, and streaming patterns using technologies like Snowflake, Databricks, BigQuery, Redshift, Iceberg, Delta Lake, or Hudi.
• Design data pipelines balancing latency, cost, reliability, and maintainability for batch and streaming workloads.
• Lead integration of governance, lineage, and catalog tools such as Collibra, Alation, Atlan, Unity Catalog, or DataHub.
• Define security architecture including controls, masking, encryption, and identity-aware access.
• Collaborate with ML, BI, and product teams to align platform capabilities with consumption needs.
• Establish data contract and product principles to promote ownership, quality, and decoupling.
• Lead architecture reviews and guide pipeline and warehouse design proposals.
• Drive cost optimization and capacity planning across the data platform.
• Design disaster recovery, multi-region, and high-availability strategies.
• Mentor data engineers and architects on standards and best practices.
• Produce architecture documentation such as context diagrams and decision records.
• Stay current with data platform research and ecosystem developments.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Information Systems, or related field.
• Eight or more years of experience in data engineering with significant architecture experience.
• Expertise in at least two major data platforms such as Snowflake, Databricks, BigQuery, or Redshift.
• Strong understanding of lakehouse architectures, modern table formats, and streaming systems.
• Hands-on experience with Spark, Flink, or Kafka at production scale.
• Strong data modeling skills across dimensional, normalized, and data-vault patterns.
• Experience with governance, lineage, and catalog implementations.
• Knowledge of cloud platforms, networking, identity, and cost optimization.
• Excellent communication and stakeholder management skills.
• Proven track record leading large data platform initiatives.

Pay

Salary Range: $100,000–$150,000 annually.