AI Data Analytics Engineer

Role Overview

Workplace

• This position works onsite five days a week in Lisle, Illinois.

What You Will Do

• Translate engineering problems into scalable data-driven applications and services integrated with internal systems.
• Design, implement, and maintain relational and analytical databases, including schemas, indexing, partitioning, backups, and migrations.
• Build ETL/ELT pipelines and data ingestion systems for enterprise sources including MES, ERP/SAP, CRM, warranty, and field records.
• Develop backend REST and gRPC services for analytics, AI agent outputs, and application data.
• Implement frontend dashboards and interactive user interfaces for insights and engineering workflows.
• Design and orchestrate agentic AI workflows that automate code generation, code review, data analysis, testing, and reporting.
• Ensure application reliability, observability, security, and data governance.
• Implement CI/CD for code, database migrations, and agentic workflow deployments.
• Optimize query performance and schemas for analytics and high-ingest workloads.
• Produce architecture documentation, data contracts, and operational runbooks.
• Enable knowledge transfer and training for stakeholders.

Basic Qualifications

• A bachelor's or master's degree in computer science, data science, software engineering, applied mathematics, or equivalent experience.
• At least 2 years of experience building production software, data systems, or analytics platforms.
• Strong Python skills and experience with APIs such as FastAPI or Flask.
• Advanced SQL expertise and relational database design experience.
• Experience with data warehouses, columnar stores, or time-series databases.
• Experience with ETL/ELT orchestration and incremental load strategies.
• Hands-on experience with AI coding agents and agentic development tools.
• Experience designing and orchestrating multi-step agentic AI workflows.
• Experience with containerization, orchestration, and CI/CD tools.
• Experience building dashboards and visualizations.
• Strong software engineering practices including testing, code reviews, CI, and documentation.
• Excellent communication and cross-functional collaboration skills.

Technical Skills

• Relevant technologies include PostgreSQL, MySQL, SQL Server, BigQuery, Redshift, Snowflake, TimescaleDB, InfluxDB, Airflow, dbt, Spark, Docker, Kubernetes, GitHub Actions, Jenkins, Power BI, Tableau, Dash, React, FastAPI, Flask, LangChain, LangGraph, AutoGen, and CrewAI.

Preferred Qualifications

• Experience with Kafka or RabbitMQ for event-driven pipelines.
• Experience with prompt engineering, agent evaluation, observability tooling, and guardrails.
• Contributions to open-source agentic frameworks or projects showcasing autonomous coding agents.
• Experience with Flyway, Alembic, or other database migration tooling.
• Familiarity with AWS, GCP, or Azure data architectures and security practices.
• Experience building custom AI agent tools and integrations with enterprise systems.

Compensation

• The anticipated salary range is $90,000 to $110,000 per year.
• The role is eligible for variable pay issued as a monetary bonus or in another form.

Company Context