Data Engineer, Forward Deployed Engineer

The Role

At Kyndryl, we don't just build technology-we deploy it where it matters most, driving scalable technology modernization and mission-critical transformations for the world's leading enterprises. Within our newly established Lab, we design, build, and deploy real-world enterprise technology where it creates the greatest physical impact. We operate under a modern triad delivery model, combining deep engineering, design, and business strategy to deliver outcomes that keep global industries moving forward.

As a Forward Deployed Data Engineer, you are the builder whom customers ask for by name. You will serve as a critical bridge between complex business challenges and scalable data solutions, operating at the intersection of AI innovation and real-world impact. Operating as a technical anchor, you will design, deploy, and refine the high-performance data infrastructure, pipelines, and context engines that fuel next-generation artificial intelligence, machine learning, and autonomous workflows in live customer environments.

This is a dynamic, highly collaborative, and hands-on role. You will take true ownership of outcomes, moving quickly from scoping and building initial proof-of-concepts to deploying hardened, production-ready systems that generate immediate business value for our customers.

• This is a hybrid role requiring a minimum of 3 days per week on-site in Frisco, TX. Candidates must reside within a commutable distance, as relocation assistance will not be provided.

Forward Deployed Pipeline Architecture & Optimization

• Design, optimize, and maintain scalable ETL/ELT pipelines to support high-volume batch processing and low-latency real-time streaming.
• Architect distributed systems and database models across hybrid and cloud-native environments, ensuring they are optimized for performance, scale, and cost.
• Diagnose, debug, and resolve complex performance bottlenecks across diverse database schemas and distributed data layers.

AI Grounding & Context Engineering

• Deploy, index, and manage vector databases and semantic layers specifically tailored for high-context AI search, retrieval-augmented generation (RAG), and agent memory structures.
• Construct robust, secure, and high-throughput API endpoints that enable autonomous systems to interact dynamically with complex, distributed datasets.
• Design and configure feature stores to support active machine learning pipelines and real-time inference loops.

Data Quality, Observability & Compliance

• Implement modern data quality and pipeline observability frameworks to ensure clean, high-fidelity data delivery to downstream systems.
• Log pipeline activities, track metadata lineage, and set up automated testing loops to systematically prevent schema drift.
• Ensure all built technical solutions align seamlessly with strict industry compliance, security, and data protection regulations.

Field Intelligence & Platform Evolution

• Capture deployment insights, document real-world best practices, and feed these learnings back into Kyndryl's core technology platforms and frameworks to accelerate future customer implementations.
• Collaborate seamlessly across global teams and practices, cutting through organizational silos to prioritize the right customer outcome.
• Balance rapid software delivery and field prototyping with long-term platform stability, reducing technical debt as solutions mature.

Kyndryl currently does not require employees to be fully vaccinated against COVID-19, however, if you are hired to work at a client, customer, or partner location, you may be required to show proof of vaccination to align with their respective COVID-19 vaccination policies. Those who believe they are eligible may apply for a medical or religious accommodation prior to the start of employment.

Who You Are

• You're good at what you do and possess the required experience to prove it.
• However, equally as important - you have a growth mindset; keen to drive your own personal and professional development.
• You are customer-focused - someone who prioritizes customer success in their work.
• And finally, you're open and borderless - naturally inclusive in how you work with others.

As a Forward Deployed Engineer, you thrive in dynamic, fast-moving environments and are highly comfortable navigating ambiguity. You are passionate about translating messy, real-world data challenges into elegant software solutions, and you value building strong, trust-based relationships with both technical teams and client stakeholders.

Required Skills and Experience

• Strong, production-grade coding proficiency in Python and advanced SQL optimization.
• Practical experience designing, building, and orchestrating ETL/ELT pipelines using tools such as Airflow, dbt, and Kafka.
• Extensive technical expertise in database modeling, distributed computing, and deploying resources within cloud-native environments (AWS, Azure, or GCP).
• Hands-on experience implementing vector databases (e.g., Pinecone, Milvus, Chroma, Weaviate) and vector indexing strategies for high-context search.
• Working knowledge of data quality, pipeline lineage, and modern data observability tools (e.g., Great Expectations, DataHub).
• Cloud-native technical certifications on AWS, Azure, or GCP, or a demonstrated willingness to achieve certifications during your journey with us.
• Bachelor's degree in Computer Science, Data Science, Engineering, or a closely related technical field, or equivalent practical professional experience.

Preferred Skills and Experience

• Prior experience designing and implementing data pipelines in highly regulated industries, such as Financial Services, Healthcare, or the Public Sector.
• Hands-on experience scaling deployments using containerization tools such as Docker and Kubernetes.
• Familiarity with emerging semantic modeling techniques, metadata management, and modern integration patterns for AI agent architectures.
• Experience building and monitoring CI/CD pipelines, utilizing version control (Git & GitHub), and delivering software under Agile methodologies.
• Advanced technical certifications in specialized database engineering, data architecture, or machine learning.
• Master's degree in Computer Science, Data Engineering, or a related discipline.