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AI Data Analytics Engineer

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Salary

$90,000 - $110,000

Location

Lisle, IL

Posted

Today

We are seeking an experienced AI Data Analytics Engineer to accelerate data-driven engineering across Molex’s Optical Connectivity product portfolio. This hands-on role blends agentic AI workflow development, data analytics, database engineering, and full-stack application development to deliver robust databases, ETL pipelines, APIs, dashboards, and AI-agent-powered services that convert test and operational data into actionable insights. The ideal candidate is fluent in modern AI coding agents (e.g., OpenAI Codex, Claude Code, GitHub Copilot) and skilled at designing autonomous and semi-autonomous agentic workflows that accelerate software delivery, testing, and engineering decision-making.

What you will do

  • 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.

Who you are (basic 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) for automated code generation, refactoring, and testing.
  • Experience designing and orchestrating agentic AI workflows (multi-step reasoning, tool/function calling, retrieval-augmented generation) using frameworks such as 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.

What will put you ahead

  • Experience with message brokers/streaming (Kafka, RabbitMQ) for event-driven agentic pipelines.
  • Experience with prompt engineering, agent evaluation/observability tooling (e.g., LangSmith, Helicone), and guardrails for safe, reliable autonomous agent behavior.
  • Contributions to open-source agentic frameworks or personal/professional projects showcasing autonomous coding agents, agent-to-agent orchestration, or AI-driven developer tooling.
  • Experience with database migration tooling and schema versioning (Flyway, Alembic).
  • Familiarity with cloud-native data architectures (AWS/GCP/Azure) and security/compliance practices for proprietary data.
  • Experience building custom AI agent tools and integrations (e.g., MCP servers, plugin/extension architectures) to connect agentic workflows with enterprise systems (SAP/xRPM, Power Automate, Salesforce).

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