Senior AI/Data Engineer

This role is responsible for defining and leading the engineering approach for complex, data-driven and AI-enabled features that deliver measurable business outcomes through customer insights. As a senior member of the team, you will serve as a technical thought leader and hands-on contributor, partnering with internal teams to design and deliver scalable analytics, AI, and agentic intelligence solutions.


Responsibilities:

• Lead the engineering design and implementation of enterprise-scale data, analytics, and AI platforms
• Design and deliver end-to-end solutions from architecture through implementation and production support
• Apply deep expertise in big data and real-time processing technologies, including Hadoop, Spark, Kafka, and Spark Streaming
• Engineer data pipelines and feature stores that reliably power machine learning models and real-time scoring
• Define and implement data and AI engineering best practices, ensuring solutions are scalable, resilient, and secure
• Provide technical thought leadership across modern data, AI, and analytics platforms
• Collaborate effectively with onshore and offshore engineering, data science, and product teams
• Function as a senior individual contributor while also leading teams or workstreams at the program level
• Act as a trusted technical advisor, translating business needs into data-driven and AI-powered solutions

• Proven experience delivering complex, enterprise-scale data and analytics platforms
• Strong hands-on expertise with distributed data processing and streaming architectures (Hadoop, Spark, Kafka, Spark Streaming)
• Experience supporting machine learning and AI workloads, such as feature engineering, model input pipelines, and real-time inference
• Experience with NoSQL and low-latency data stores (e.g., Redis) supporting real-time analytics and AI inference
• Demonstrated ability to lead solution design and delivery across multiple teams
• Excellent collaboration and communication skills, with experience working across geographically distributed teams
• Proficiency in Data Integration and Data Security within real-time and Big Data ecosystems, including knowledge of Kerberos

• Familiarity with agentic or autonomous processing patterns (e.g., event-driven workflows, rules-plus-AI decisioning) is highly desirable
• Experience with additional real-time streaming technologies like Flink or Storm
• Familiarity with Cloud Technologies such as Azure, AWS, or GCP
• Working knowledge of machine learning algorithms, statistical analysis, and programming languages (Python or R)
• Strong command of Visual Analytics Tools, with a focus on Tableau