Join Client as a Staff Engineer in Data and AI, where you will shape the technical direction of our data pipeline and AI platform. This role involves driving architectural decisions, mentoring engineering talent, and delivering critical platform enhancements during a significant period of transition.

Our current data environment leverages SQL Server CDC, Confluent/RedPanda, Redshift (Bronze/Silver/Gold) via DBT, EC2, DynamoDB, and AWS Bedrock, with Snowflake being phased out. Approximately 90% of our data is managed internally.

Key responsibilities include designing and implementing complex data pipelines across Redshift, MSK/RedPanda, DBT, and S3. You will establish engineering standards and best practices for the Data and AI platform team. This role also involves leading technical design for AI/ML infrastructure, including AWS Bedrock integrations and Claude-based workflows.

Further duties encompass driving data ingestion standardization and canonical ID resolution as a company-wide initiative, collaborating with ML Engineers on data infrastructure for model training and inference, and implementing data quality controls and observability using Coralogix and Grafana. You will also contribute to PCI DSS-compliant data handling, including PAN masking, PII controls, and TonicAI integration, alongside mentoring Lead and Senior Engineers.

We are seeking candidates with 6–10 years of experience in data engineering or AI platform engineering. Essential skills include expert-level experience with AWS data services like EKS, ECS, Lambda, S3, and EC2.

Strong hands-on experience with Redshift and the medallion/Bronze-Silver-Gold architecture is required, along with proficiency in DBT for data transformation at scale. Familiarity with SQL Server CDC-based ingestion pipelines and event streaming platforms such as Confluent, RedPanda, or Kafka is necessary.

Experience in building ML-ready data pipelines and feature engineering infrastructure is crucial. Candidates should also be familiar with AWS Bedrock and GenAI pipeline patterns, possess a strong understanding of PCI DSS data handling requirements, and demonstrate the ability to set technical direction and mentor engineers.