IT Data Engineer II

IT Data Engineer II

Contract Type:

Contractor

Location:

Juno Beach

Industry:

Utilities

Contact Name:

Taylor Proudfoot

Contact Phone:

Date Published:

26-Jan-2026

IT Data Engineer II

📍 Location: Juno Beach, FL (Onsite)

🕒 Duration: 6-Month Contract

💰 Pay Range:$38–$42/hour



Position Overview

We’re seeking a Data Engineer with 3+ years of hands-on experience in data cleaning, transformation, and analysis using Python. This role is ideal for someone comfortable working with large, messy datasets who brings a strong analytical mindset and curiosity for modern data technologies.

Experience with machine learning and LLMs is a strong plus.


Key Responsibilities

  • Clean, preprocess, and transform structured and unstructured data using Python
  • Perform exploratory data analysis (EDA) to uncover trends and insights
  • Build reusable data pipelines and feature-engineering workflows
  • Work with SQL and cloud-based data warehouses to extract and prepare data
  • Partner with stakeholders to translate business problems into data-driven solutions
  • Develop and maintain analytical models and dashboards
  • Apply basic to intermediate machine-learning techniques where applicable
  • Experiment with and support LLM-based solutions(prompting, embeddings, APIs)
  • Ensure data quality, reliability, and proper documentation

Required Skills & Qualifications

  • 3+ years of experience as a Data Engineer or Data Analyst
  • Strong proficiency in Python for data manipulation and analysis
    • Pandas, NumPy, SciPy
  • Solid understanding of data cleaning, transformation, and feature engineering
  • Experience with SQL(PostgreSQL, MySQL, BigQuery, Snowflake, etc.)
  • Familiarity with data visualization tools
    • Matplotlib, Seaborn, Plotly, Power BI, or Tableau
  • Strong foundation in statistics and data analysis
  • Experience working with APIs and external data sources
  • Excellent problem-solving and communication skills

Preferred / Modern Tech Stack

  • Python (3.x)
  • Pandas, NumPy, Scikit-learn
  • Jupyter, VS Code
  • Git / GitHub
  • Cloud platforms: AWS, Azure, or GCP
  • Data tools: Airflow, dbt, Spark (basic exposure)
  • Docker (nice to have)

Nice to Have

  • Hands-on experience with machine-learning models
    • Regression, classification, clustering, time series
  • Exposure to LLMs & Generative AI
    • OpenAI / Azure OpenAI APIs
    • Prompt engineering
    • Embeddings & vector databases (FAISS, Pinecone, Chroma)
  • Experience with NLP or text analytics
  • Understanding of MLOps fundamentals (model versioning, monitoring)



...

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