Data Engineer IV- #26-25842
About The Position
The Data Engineer IV will lead hands-on development and provide technical direction, code reviews, and engineering oversight across multiple initiatives. The role involves establishing development environments, infrastructure standards, security controls, and migration strategies across AWS accounts and environments, as well as architecting, developing, and governing enterprise-scale data pipelines, ETL processes, ingestion frameworks, and orchestration workflows. This position identifies data gaps, develops remediation plans, and implements scalable automation to improve organizational analytics. It designs reliable data pipelines emphasizing quality, observability, resiliency, and operational supportability, and builds and optimizes large-scale data warehousing solutions for business-user experience and system performance. The engineer drives technical decisions and architectural direction, communicates with technical and non-technical stakeholders, mentors engineers, and leads cross-functional initiatives involving engineering, analytics, architecture, platform teams, and business stakeholders. Candidates should be comfortable working in a hybrid environment and collaborating with teams across multiple locations.
Requirements
- Proficiency in Python, SQL, Spark, and Generative AI technologies for scalable data and analytics solutions.
- Hands-on experience with AWS, Clienture, Databricks, and cloud-based AI/data platforms.
- Knowledge of LLMs, Retrieval-Augmented Generation (RAG), vector databases, and AI-powered search solutions.
- Strong understanding of responsible AI, data governance, data quality, security, and AI compliance practices.
- Strong problem-solving and leadership skills, including the ability to manage competing priorities in a fast-paced enterprise environment.
Nice To Haves
- Experience implementing enterprise data governance and metadata management platforms.
- Experience with real-time analytics, event-driven architectures, and streaming data platforms.
- Knowledge of modern data architecture patterns, including Data Mesh, Lakehouse, and domain-oriented design.
- Experience leading large-scale cloud transformation or enterprise data modernization programs.
- Experience creating AI applications using AWS Bedrock or similar Generative AI platforms.
- Experience building AI-ready data pipelines and ML workflows, including feature engineering and MLOps.
- AWS Certified Data Engineer, AWS Solutions Architect, or equivalent cloud certifications.
Responsibilities
- Lead hands-on development efforts and provide technical direction, code reviews, and engineering oversight across multiple initiatives.
- Establish development environments, infrastructure standards, security controls, and migration strategies across AWS accounts and environments.
- Architect, develop, and govern enterprise-scale data pipelines, ETL processes, data ingestion frameworks, and orchestration workflows.
- Identify data gaps, define remediation plans, and implement scalable automation solutions to improve analytical capabilities.
- Design and implement reliable data pipelines with emphasis on data quality, observability, resiliency, and operational supportability.
- Build and optimize large-scale data warehousing solutions with attention to business-user experience and system performance.
- Drive technical decision-making, influence architectural direction, and communicate complex technical concepts to technical and non-technical stakeholders.
- Mentor engineers, foster technical growth, and help build high-performing data engineering teams.
- Lead cross-functional initiatives involving data engineering, analytics, architecture, platform engineering, and business stakeholders.
- Manage competing priorities in a fast-paced enterprise environment.
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What This Job Offers
Career Level
Senior
Education Level
No Education Listed
