Principal Data Engineer
Core
Design and build scalable, high-throughput Big Data systems and foundational data infrastructure to support real-time and batch processing for business planning workflows and AI initiatives.
Role type
Principal Data Engineer (Full Stack)
Builds
Scalable data platforms, ETL/ELT pipelines, API services, data lakes, warehouses, and streaming architectures.
Domain
Enterprise Planning / Big Data / AI Infrastructure
Deliverable
production ML models | infrastructure
Required skills
Distributed computing frameworks (Apache Spark, Flink, Hadoop), Message brokers and event streaming (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, Modern software development practices (CI/CD, IaC)
Preferred skills
Cloud-native infrastructure (AWS, GCP, Azure), Data observability and monitoring frameworks, Technical leadership and mentoring
Technologies
Apache Spark, Apache Flink, Apache Kafka, Apache Airflow, Snowflake, BigQuery, Databricks, Delta Lake, Python, SQL
Responsibilities
Lead data architecture design and deployment of scalable Big Data systems; Architect and manage foundational data systems including vector, NoSQL, and document databases; Develop end-to-end data engineering solutions including ETL/ELT pipelines and API services; Design storage and processing layers for analytics workloads; Engineer context pipelines balancing batch and streaming patterns; Optimize distributed queries and data transformations for high performance; Implement data quality frameworks for integrity and governance; Collaborate with teams to build data models capturing customer metrics semantics.
Seniority
Principal, hands-on IC with strategic direction
