AI Data Platform Engineer

This is a Fully Remote Job

About Our Client:

The organization operates in technology consulting and software development, delivering cloud, artificial intelligence, data, and enterprise solutions across the United States. It addresses challenges related to integrating and optimizing data and AI technologies to support enterprise-scale solutions.

About the Opportunity:

The AI DATA PLATFORM ENGINEER role is responsible for defining and leading the architecture of the enterprise data platform across ingestion, storage, processing, governance, and consumption layers. This position sets standards and strategic direction for data infrastructure and collaborates with multiple teams to establish a scalable and coherent data foundation that supports analytics, machine learning, and business needs.

Responsibilities:

• Define target 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 end-to-end data pipelines balancing latency, cost, reliability, and maintainability.
• Lead integration of governance, lineage, and catalog tools such as Collibra, Alation, Atlan, Unity Catalog, or DataHub.
• Define security architecture including row/column 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.
• Conduct architecture reviews and guide pipeline and warehouse design across teams.
• Drive cost optimization and capacity planning for data platform.
• Develop disaster recovery, multi-region, and high-availability strategies.
• Mentor data engineers and architects on standards and best practices.
• Produce architecture artifacts such as context diagrams and decision records.
• Stay updated on data platform research, vendor offerings, and open-source developments.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Information Systems, or related field.
• Eight or more years in data engineering with significant architecture experience.
• Expertise in at least two major data platforms (e.g., Snowflake, Databricks, BigQuery, Redshift).
• Strong understanding of lakehouse architectures, modern table formats, and streaming systems.
• Hands-on experience with Spark, Flink, or Kafka at production scale.
• Proficiency in data modeling across dimensional, normalized, and data-vault patterns.
• Experience implementing governance, lineage, and catalog capabilities.
• Solid knowledge of cloud platforms, networking, identity, and cost optimization.
• Strong communication, facilitation, and stakeholder management skills.
• Proven leadership of large data platform initiatives across teams.

Pay Range and Compensation Package:

• Salary range is $135,000 to $170,000 annually.

Equal Opportunity Statement: Our client is an equal opportunity employer. They celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, or national origin.

Note:

TalentHop is a recruitment partner of this role. Please note that all employment decisions, including candidate assessment, interviews, hiring, compensation, and employment terms, are made exclusively by the hiring employer.