Experience: 5+ years of software development experience, either in a core product engineering role or a customer-facing sales/solutions engineering role.
Hands-on big data analytics/cloud experience.
Understanding of how data is secured in transit and at rest, authentication & authorization standards, and RBAC.
Expert SQL and data modeling expertise.
AI/ML, MCP experience a plus.
Systems design & architecture: Proven ability to design and implement end-to-end data solutions in production environments.
Proficient in one or more of Python, Node.js, Java, and C/C++.
Production experience debugging distributed systems, tuning for latency, logging & monitoring, performance telemetry experience a plus.
Prioritize user value, MVP iteration, and long-term scale .
Expert-level SQL with hands-on experience building/maintaining data pipelines (ETL/ELT, tools like Airflow, dbt).
Extensive design and implementation experience with relational databases and general familiarity with other database paradigms, including NoSQL, graph or time series databases.
Working knowledge of popular data solutions for batch and real-time processing , e.g., Spark, Kafka, Trino, Flink, Apache ecosystem.
Exposure to data lakehouse paradigms with working knowledge of one or more: Databricks, Snowflake, BigQuery (Iceberg a plus).
Depth of systems architecture expertise, hands-on in at least one of Azure, AWS, or GCP.
May have worked as a software engineer on enterprise products or as a backend engineer.
Working knowledge of leading LLMs a big plus.
Qualifications:
Bachelor’s degree in computer science, Engineering, Information Systems, or related technical field (or equivalent practical experience).
Job Description:
Build data solutions with data originating from customers’ core systems of record, transformed through sophisticated data pipelines and landing in a format ready to be consumed by human and AI agents.
Help ground data in a business context to drive AI agent accuracy and quality.
Operate in the field, working side-by-side with customers to adapt, deploy, and iterate in live environments.
Codify reusable assets—libraries, SDKs, snippets, technical accelerators—to help customers go from zero to value rapidly.
Deliver production-ready solutions in agile end-to-end sprints – with frequent customer interaction, both async and live over Zoom/Teams.
Operate with agility: integrate with legacy systems, navigate ambiguity, ship working builds at speed.
Codify patterns: build scaffolds, SDKs, and documentation to scale success across customers.
Influence platform: inform product strategy through field-tested insights and extensible code.
Partner with live customers and internal teams to design, implement, and deliver solution-ready builds in agile sprints. Your software becomes the reference implementation for scalable Data + AI implementations across our customer base. Influence the core product roadmap through regular touchpoints with WDF engineering teams.