Lisle‑Based AI Data Analytics Engineer

Flint Hills Resources; Lisle (IL); On-site; USD 90,000 - 110,000; Full time

Job summary

Molex’s Optical Connectivity Group in Lisle, IL seeks an experienced AI Data Analytics Engineer to accelerate data-driven engineering across its product portfolio.

The role blends agentic AI workflow development, data analytics, database engineering, and full-stack development to deliver robust databases, ETL pipelines, APIs, dashboards, and AI-powered services that convert test and operational data into actionable insights.

Qualifications

• BS or MS in Computer Science, Data Science, Software Engineering, Applied Math, or equivalent experience.
• 2+ years of experience building production software, data systems, or analytics platforms (backend, DB, or data engineering).
• Strong Python skills; experience with APIs (FastAPI, Flask) and web services.
• Advanced SQL expertise and relational database design experience (PostgreSQL, MySQL, SQL Server).
• Experience with data warehousing / columnar stores (BigQuery, Redshift, Snowflake) or time-series DBs (TimescaleDB, InfluxDB).
• Experience with ETL/ELT orchestration (Airflow, dbt, Spark) and incremental load strategies.
• Hands-on experience with AI coding agents and agentic development tools (e.g., OpenAI Codex, Claude Code, GitHub Copilot).
• Experience designing and orchestrating agentic AI workflows (multi-step reasoning, tool/function calling, retrieval-augmented generation) using LangChain, LangGraph, AutoGen, or CrewAI.
• Experience with containerization and orchestration (Docker, Kubernetes) and CI/CD tools (GitHub Actions, Jenkins).
• Experience building dashboards and visualizations (Power BI, Tableau, Dash, React).
• Strong software engineering practices: unit/integration testing, code reviews, CI, and documentation.
• Excellent communication and cross-functional collaboration skills.

Responsibilities

• Translate engineering problems into data-driven applications and services that scale and integrate with internal systems.
• Design, implement, and maintain relational and analytical databases (logical/physical schema design, indexing, partitioning, backups, migrations).
• Build reliable ETL/ELT pipelines and data ingestion systems for heterogeneous enterprise sources (MES, ERP/SAP, CRM, warranty/field records).
• Develop backend services and APIs (REST/gRPC) to serve analytics, AI agent outputs, and application data to dashboards, lab tools, and internal apps.
• Implement frontend dashboards and interactive UIs (Power BI/Tableau, Dash/React) to present insights and enable engineer workflows.
• Design, build, and orchestrate agentic AI workflows — multi-step, tool-using AI agents that automate engineering tasks such as code generation, code review, data analysis, testing, and reporting; leverage AI coding agents (OpenAI Codex, Claude Code) to accelerate development velocity.
• Ensure application reliability, observability, security (logging, metrics, RBAC, encryption at rest/in‑flight) and data governance.
• Implement CI/CD for code, database schema migrations, and agentic workflow deployment; enforce automated testing and rollback strategies.
• Optimize query performance and schema for analytics workloads and high-ingest scenarios.
• Produce architecture docs, data contracts, and operational runbooks; enable knowledge transfer and training for stakeholders.

Skills

Python

APIs

SQL

Data warehousing

ETL/ELT

AI agents

Dash/React

Power BI

Tableau

CI/CD

Docker

Kubernetes

LangChain

Education

Bachelor's/Master's in CS/DS/SE/Applied Math

Tools

FastAPI

Flask

PostgreSQL

MySQL

SQL Server

BigQuery

Redshift

Snowflake

TimescaleDB

InfluxDB

Airflow

dbt

Spark

OpenAI Codex

Claude Code

GitHub Copilot

LangGraph

AutoGen

CrewAI

Docker

Kubernetes

GitHub Actions

Jenkins

Power BI

Tableau

Dash

React

Job description

Molex’s Optical Connectivity Group in Lisle, IL seeks an experienced AI Data Analytics Engineer to accelerate data-driven engineering across its product portfolio.

The role blends agentic AI workflow development, data analytics, database engineering, and full-stack development to deliver robust databases, ETL pipelines, APIs, dashboards, and AI-powered services that convert test and operational data into actionable insights.