AVP, Principal Data Engineer (L11)

Design, develop, and lead production-grade data engineering applications across agile teams, combining hands-on coding with technical leadership, design reviews, and end-to-end delivery ownership.Design and implement scalable ELT/ETL and 24x7 real-time event streaming pipelines using Ab Initio Continuous Flows/Spark Streaming and Kafka ecosystems (AWS MSK and Confluent Kafka), ensuring fault tolerance, strong delivery guarantees (idempotency/exactly-once where applicable), and near-zero downtime deployments.Own event-driven data workflows that process high-throughput, low-latency financial transactions across mission-critical systems, and build/operate Lakehouse data infrastructure on AWS (S3, Glue, EMR, Redshift), using Ab Initio (must-have) and Spark as core engineering tool.Develop AI-ready data products and feature pipelines for downstream analytics and operational AI use cases, and lead cloud migration efforts to modernize legacy batch ETL into cloud-native, event-driven architecture.Collaborate with solution architects to translate designs into robust, scalable implementations; partner with product owners and program managers in a SAFe/Scaled Agile environment to align delivery with business priorities.Define and enforce data engineering standards, coding best practices, CI/CD, and DevOps processes; mentor engineers and foster a culture of engineering excellence and continuous learning. Required Skills/Knowledge: Bachelors degree in Computer Science, Engineering, or related field with 8+ years of experience in ELT/ETL, data warehousing, or Lakehouse engineering; or, in lieu of a degree with 10+ years of equivalent hands-on experience.8+ years of full lifecycle data engineering experience (design, development, testing, documentation, performance tuning, and production support) across large-scale technologies including Ab Initio, Kafka (MSK/Confluent), Spark, Hive, RDBMS (Oracle/MySQL), and AWS services (EMR, MSK, Glue, S3, Redshift, IAM).5+ years of experience with 24x7 real-time/streaming pipelines and 2+ years with AWS cloud platform engineering, including infrastructure-as-code and containerized workloads.Experience leading or mentoring data engineering teams in an Agile/SAFe delivery environment.Ability to travel for business as needed. Desired Skills/Knowledge: Proven experience as a hands-on data engineering technical lead in a SAFe environment, owning mission-critical data platform applications with end-to-end accountability across batch and real-time pipelines in a DevOps model.Experience in FinTech, credit card, or banking environments handling sensitive data in a regulated context, with the ability to communicate complex technical topics and influence decisions across IT and business stakeholders.AWS Solutions Architect or AWS Data Engineer certification (or actively pursuing). Exposure to .