Manage and mentor team of data engineers
Implement a strategic roadmap to modernize legacy data and analytics ecosystems using Cloud and AI
Solve for data complexity by enabling data domains and data products for all consumption architypes and stakeholders including reporting, data science, AI/ML and analytics
Effectively communicate strategy, execution progress, and outcomes to diverse stakeholders
Implement AI data pipelines that integrate structured, semi-structured, and unstructured data to support AI and Agentic solutions
Design, build and maintain scalable real-time data pipelines for efficient ingestion, processing, and delivery
Drive best practices in AI data engineering by establishing standardized processes, promoting cutting-edge technologies, and ensuring data quality and compliance across the enterprise
Oversee the design, development, and maintenance of data pipelines, data warehouses, data lakes and reporting systems
Identify and champion developer productivity improvements across the end-to-end data management lifecycle
Define and implement robust data management frameworks to ensure successful adoption of Enterprise Data Governance and Data Quality practices
Effectively manage the budget and financials for the portfolio.

Requirements

Candidates must be authorized to work in the US without company sponsorship
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field
8+ years of data engineering experience including Data solutions, SQL and NoSQL, Snowflake, ETL/ELT tools, CICD, Bigdata, Cloud Technologies (AWS/Google/AZURE), Python/Spark, Datamesh, Datalake or Data Fabric
Specialized data engineering experience focused on supporting Generative AI technologies
Strong hands-on experience implementing production ready enterprise grade AI data solutions
Experience with prompt engineering techniques for large language models
Experience in implementing Retrieval-Augmented Generation (RAG) pipelines, integrating retrieval mechanisms with language models
Experience of vector databases and graph databases, including implementation and optimization
Experience in processing and leveraging unstructured data for AI applications
Proficiency in implementing scalable AI driven data systems supporting agentic solution (AWS Lambda, S3, EC2, Langchain, Langgraph)
Strong programming skills in Python and familiarity with deep learning frameworks such as PyTorch or TensorFlow
Experience with building AI pipelines that bring together structured, semi-structured and unstructured data
Experience in implementing data governance practices, including Data Quality, Lineage, Data Catalogue capture, holistically, strategically, and dynamically on a large-scale data platform
Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes)
Strong written and verbal communication skills and ability to explain technical concepts to various stakeholders.

Benefits

Other rewards may include short-term or annual bonuses
long-term incentives
on-the-spot recognition

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data engineeringSQLNoSQLSnowflakeETLELTPythonSparkAI data solutionsdata governance

Soft Skills

mentoringcommunicationstrategic planningproblem-solvingbudget managementstakeholder engagementdeveloper productivity improvementdata quality assuranceteam leadershipexecution progress reporting

Certifications

Bachelor's degree in Computer ScienceMaster's degree in Artificial Intelligence