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Data Engineer (AI/Analytics Pipeline)

Wakapi
Lincolnshire
2 days ago
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Overview

Data Engineer (AI/Analytics Pipeline) at Wakapi. We are looking for a motivated and intellectually curious Data Engineer to join our growing Data Science and Solutions team. This role is ideal for someone passionate about AI, data integration, and building modern data infrastructure. You will play a key role in scaling and optimizing our AI and analytics platform by developing robust, secure, and scalable data pipelines in Databricks on AWS. You’ll collaborate closely with AI/ML experts, backend and frontend engineers, and product stakeholders to transform data into impactful insights and intelligent user experiences. If you're eager to work in a dynamic, remote-first environment where your contributions directly influence real-world outcomes, we want to hear from you.


Responsibilities


  • Data Pipeline Development: Design, build, and maintain ETL/ELT pipelines in Databricks to ingest, clean, and transform data from a variety of sources.
  • Data access enablement: Develop gold layer tables in a Lakehouse architecture to support machine learning models and real-time APIs.
  • Data quality and observability: Monitor data quality, lineage, and reliability leveraging Databricks best practices and observability tools.


AI-Driven Data Access Enablement


  • Collaborate with AI/ML teams to structure and model data for natural language prompts, semantic retrieval, and vector search using Unity Catalog metadata.
  • Contribute to the development of data interfaces and agent tools for secure, role-based access to structured and unstructured data.


API & Serverless Backend Integration


  • Partner with backend engineers to create serverless APIs (e.g., AWS Lambda + TypeScript) that expose curated data for front-end applications.
  • Implement scalable, secure, and performant APIs with a strong focus on data governance and compliance.
  • Develop infrastructure-as-code and monitoring frameworks to support multi-tenant scaling of pipelines and AI endpoints.


Requirements


  • 3+ years of experience as a Data Engineer or similar role in agile, distributed environments.
  • Hands-on expertise with Databricks, including workflow orchestration, CDC, and medallion architecture.
  • Strong skills in Spark or Scala for data wrangling and transformation across complex datasets.
  • Experience with CI/CD pipelines, test-driven development, and understanding of MLOps/AIOps best practices.
  • Proven ability to collaborate effectively with cross-functional teams, including product managers, engineers, and data scientists.


Preferred Skills


  • Experience with AWS Lambda (Node.js/TypeScript) and API Gateway or other serverless frameworks.
  • Understanding of API design principles and familiarity with RESTful and/or GraphQL endpoints.
  • Exposure to React-based frontend architectures and awareness of how backend data delivery impacts UI/UX performance.
  • Experience with A/B testing, experimentation frameworks, and logging for model inference and user analytics.


Additional Details


  • Seniority level — Mid-Senior level
  • Employment type — Full-time
  • Job function — Information Technology
  • Industries — Software Development


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