Overview

Role Title : AVP, Principal Data Engineer (L11)

Responsibilities

• 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.

Qualifications

• Bachelor’s 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.
• Ability to travel for business as needed.
• 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.
• AWS Solutions Architect or AWS Data Engineer certification (or actively pursuing). Exposure to agentic AI or LLM-integrated data workflows is a plus.
• Thought leadership such as articles, publications, or open-source contributions in data engineering or cloud data platforms is a plus.
• Understand the criteria or mandatory skills required for the role, before applying
• Inform your manager or HRM before applying for the role on Workday
• Ensure that your professional profile is updated (fields such as education, prior experience, skills) and it is mandatory to upload your updated resume (Word or PDF format)
• Must not be any corrective action plan (First Formal/Final Formal, LPP)
• L09+ Employees who have completed 18 months in the organization and 12 months in current role and level are only eligible
• L09+ Employees can apply
• Bachelor's degree in Computer Science, Engineering, or related field with 8+ years of experience in ELT/ETL, Data Warehousing, or large-scale data platform engineering on distributed systems and public cloud (AWS preferred).