AI Data Engineer – Modernization, AI Infrastructure

🔥 13 hours ago

🦞 Maine – Remote

🦞 Maine – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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WEX

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 1983

🏥 Healthcare

📦 Logistics

✈️ Travel

💰 $310M Post-IPO Debt on 2020-06

Healthcare • Logistics • Travel

WEX is a global commerce platform specializing in various business solutions to address operational challenges. They provide services in managing and mobilizing fleets with their fuel card systems, offering comprehensive fleet management and analytics. Additionally, they focus on business payments solutions that streamline processes across industries, enhancing efficiency and security. WEX is also involved in employee benefits administration, helping organizations effectively manage health and reimbursement accounts. Their diverse range of services caters to numerous sectors, emphasizing innovation, sustainability, and effective solutions for business growth.

📋 Description

• Analyze complex SQL Server stored procedures to identify embedded business logic, dependencies, and data access patterns • Refactor stored procedures to simplify data access, improve maintainability, and enable business logic to move into services • Design and execute database migrations while maintaining data integrity, availability, and backward compatibility • Analyze execution plans, optimize queries, and design indexing strategies for high-volume workloads • Implement event-driven database patterns including CDC, outbox patterns, and event publishing • Build automated tests and validation processes for database changes, migrations, and refactored procedures • Create structured, AI-consumable documentation for schemas, procedures, dependencies, and system context • Build embedding pipelines for text extraction, preprocessing, chunking, embedding generation, and vector storage • Implement and optimize vector databases, vector indexes, semantic search, and hybrid retrieval patterns • Build synchronization pipelines that keep vector stores aligned with source systems • Develop retrieval APIs and services consumed by AI applications and agents • Implement evaluation and monitoring for RAG systems, including retrieval quality, latency, relevance, and data freshness • Partner with AI/ML engineers to improve embedding strategies, retrieval quality, and AI data performance • Design and implement ETL/ELT pipelines across SQL Server, PostgreSQL, Snowflake, and cloud data services • Build API-based ingestion, event streaming, and batch-processing workflows • Implement data quality, validation, observability, and operational monitoring for data pipelines • Develop infrastructure-as-code for database provisioning and configuration using Terraform and ARM/Bicep • Support NoSQL data solutions including MongoDB and Cosmos DB, focusing on data modeling and query performance • Design data access patterns supporting domain-driven architectures, including repositories, query services, and read models • Use AI coding assistants daily for database analysis, code generation, debugging, testing, and documentation • Develop prompts, scripts, and workflows applying AI to database engineering and modernization challenges • Contribute to AI-powered engineering tools such as stored procedure analyzers, schema documentation generators, and migration assistants • Create structured context and artifacts enabling AI agents and coding tools to reason about data systems • Evaluate emerging AI tools and identify opportunities to improve engineering productivity • Partner with application, platform, and AI/ML engineers on scalable, reliable data solutions • Participate in code and architecture reviews • Troubleshoot complex production data and performance issues and contribute to operational support • Document technical decisions, patterns, and solutions for reuse across engineering teams • Mentor engineers on database design, performance optimization, data engineering, and modern engineering practices

🎯 Requirements

• Strong hands-on experience with SQL Server, T-SQL, stored procedures, query optimization, and execution plans • Proven experience modernizing legacy database systems and decomposing complex database logic into maintainable application or service architectures • Strong understanding of relational database design, indexing, transactions, data integrity, and performance engineering • Experience building production-grade data pipelines and integrating data through APIs, events, and batch processes • Experience with one or more modern data platforms such as PostgreSQL, Snowflake, MongoDB, or Cosmos DB • Practical experience with vector databases, embeddings, semantic search, RAG, or AI data pipelines • Understanding of event-driven architectures and patterns such as CDC and transactional outbox • Experience with cloud platforms and infrastructure-as-code, preferably AWS/Azure and Terraform • Strong software engineering fundamentals, including version control, automated testing, CI/CD, and code review practices • Demonstrated ability to use AI coding assistants effectively and willingness to incorporate AI into day-to-day engineering work • Experience with SQL Server, PostgreSQL, Snowflake, MongoDB, or Cosmos DB • Preferred: Experience building data infrastructure for LLM or agentic applications • Preferred: Experience with Pinecone, Azure AI Search, OpenSearch, pgvector, or similar vector databases • Preferred: Experience with Kafka or other event-streaming platforms • Preferred: Experience developing retrieval services or RAG evaluation frameworks • Preferred: Experience creating internal AI-powered developer tools or automation • Preferred: Experience working in large-scale, distributed, cloud-native environments

🏖️ Benefits

• Health, dental and vision insurances • Retirement savings plan • Paid time off • Health savings account • Flexible spending accounts • Life insurance • Disability insurance • Tuition reimbursement • Quarterly or annual bonus eligibility for non-sales roles, based on applicable plan • Comprehensive and market competitive benefits supporting personal and professional well-being