Principal Data Engineer - AI
Core
Architect and build scalable, high-throughput Big Data systems and foundational data infrastructure to power real-time and batch processing for AI initiatives and business planning workflows.
Role type
Principal Data Engineer (AI Infrastructure)
Builds
Production-grade data platforms, ETL/ELT pipelines, vector/NoSQL databases, and distributed streaming architectures.
Domain
Enterprise Planning / Big Data / AI Infrastructure
Deliverable
production ML models | infrastructure
Required skills
Distributed data processing (Apache Spark, Flink, Hadoop), Message brokers (Apache Kafka, Kinesis), Workflow orchestration (Apache Airflow, Dagster), Cloud data warehouses (Snowflake, BigQuery, Redshift), Data lake architectures (Databricks, Delta Lake, Apache Iceberg), Advanced SQL, Python, Infrastructure as Code, CI/CD, Testing.
Preferred skills
Cloud-native infrastructure (AWS, GCP, Azure), Data observability and monitoring frameworks, Enterprise planning platform experience.
Responsibilities
Lead data architecture design and deployment of scalable Big Data systems; Architect and manage foundational data systems including vector and NoSQL databases; Develop end-to-end data engineering solutions and ingestion frameworks; Design storage and processing layers for analytics workloads; Engineer context pipelines balancing batch and streaming patterns; Optimize distributed queries and data transformations; Implement data quality frameworks; Collaborate on data models capturing customer metrics and hierarchies; Evaluate new tools and technologies for adoption.
Seniority
Principal, hands-on IC with leadership and mentorship
