Analytics Engineer

Lex Products; Shelton (CT); On-site; USD 120,000 - 150,000; Full time

Job summary

Lex Products in Shelton, CT is seeking an Analytics Engineer to design and maintain data pipelines, models, and analytics tools that inform product development and manufacturing decisions.

You will collaborate with engineers, product teams, and business stakeholders to deploy predictive models, perform statistical analyses, and drive data-driven improvements across the company.

Qualifications

• Bachelor's degree in Business Analytics, Computer Science, Data Engineering, Data Science, or related field (Master’s a plus).
• 2+ years in data engineering, data science, or related role, preferably in manufacturing.
• Proficiency in SQL, Python or other programming languages for data manipulation, analysis, and data science.
• Experience with ETL tools, data warehousing, cloud platforms (AWS/Azure/Google Cloud), and ML frameworks.
• Strong data modeling, data architecture, statistical analysis, and BI tools (Power BI, Tableau, Grafana).
• Familiarity with big data technologies (Hadoop, Spark) a plus.
• Experience with ML algorithms, predictive modeling, and data science tools (TensorFlow, scikit-learn).
• Excellent problem-solving, attention to detail, and communication skills.

Responsibilities

• Design, build, and maintain scalable data pipelines for large data volumes from multiple sources.
• Ensure data is clean, reliable, and readily available for analysis and data science apps.
• Optimize data workflows for performance, cost, and maintainability.
• Develop and maintain data models reflecting key business processes; define KPIs and dashboards.
• Develop predictive models and ML algorithms to solve business problems.
• Collaborate with engineers and product teams to integrate data science into products.
• Explore new data science methodologies and tools to drive innovation.
• Provide support and training on data tools, science, and analytics best practices.
• Align data infrastructure with company goals and industry best practices.
• Identify opportunities to improve data processes, analytics tools, and methodologies.
• Stay current with industry trends in data engineering, science, and analytics.

Skills

SQL

Python

Data modeling

Statistical analysis

Machine learning

Data warehousing

Power BI/Tableau

Cross-functional collaboration

Problem solving

Education

Bachelor’s degree in related field

Master’s degree

Tools

ETL tools

AWS

Azure

Google Cloud

Hadoop

Spark

TensorFlow

scikit-learn

Grafana

Job description

Position Overview:

We are seeking a skilled and motivated Analytics Engineer to join our growing Analytics team. The successful candidate will be responsible for designing, developing, and maintaining data pipelines, models, and analytics tools that drive key business decisions. Additionally, the role will involve leveraging data science techniques to build predictive models, perform statistical analysis, and develop machine learning solutions that enhance our product development, manufacturing processes, and business strategies.

Key Responsibilities:

• Design, build, and maintain scalable data pipelines to process and analyze large volumes of data from multiple sources.
• Ensure data is clean, reliable, and readily available for analysis, reporting, and data science applications.
• Optimize data workflows for performance, cost, and maintainability.
• Data Modeling and Analysis:
  
  
  
  • Develop and maintain data models that reflect the company’s key business processes.
  
  
  • Work with cross-functional teams to define and implement KPIs, dashboards, and reporting tools.
  
  
  • Apply statistical methods and data science techniques to analyze complex datasets, identifying trends, patterns, and opportunities for improvement in manufacturing, product development, and sales strategies.
  
  
• Data Science and Machine Learning:
  
  
  
  • Develop predictive models and machine learning algorithms to solve business problems and enhance decision-making processes.
  
  
  • Collaborate with engineers and product teams to integrate data science solutions into existing products and services.
  
  
  • Continuously explore new data science methodologies and tools to drive innovation within the company.
  
  
• Collaboration and Support:
  
  
  
  • Partner with engineers, product managers, and business stakeholders to understand their data and analytics needs.
  
  
  • Provide technical support and training to team members and other departments on the use of data tools, data science, and analytics best practices.
  
  
  • Work closely with IT to ensure data infrastructure is aligned with company goals and industry best practices.
  
  
• Identify opportunities to improve existing data processes, analytics tools, and data science methodologies.
• Stay current with industry trends, tools, and technologies in data engineering, data science, and analytics.
• Contribute to the development and execution of the company's data strategy.
• Quality Assurance:
  
  
  
  • Implement data validation, testing, and documentation processes to ensure the accuracy and reliability of analytics and data science outputs.
  
  
  • Ensure compliance with data governance policies and best practices.
  
  

Qualifications:

• Bachelor’s degree in Business Analytics, Computer Science, Data Engineering, Data Science, or a related field. A Master’s degree is a plus.
• 2+ years of experience in data engineering, data science, or a related role, preferably in a manufacturing environment.
• Proficiency in SQL, Python, or other programming languages for data manipulation, analysis, and data science applications.
• Experience with ETL tools, data warehousing, cloud platforms (e.g., AWS, Azure, Google Cloud), and machine learning frameworks.
• Strong understanding of data modeling, data architecture, statistical analysis, and business intelligence tools (e.g., Power BI, Tableau, Grafana).
• Familiarity with big data technologies and frameworks (e.g., Hadoop, Spark) is a plus.
• Experience with machine learning algorithms, predictive modeling, and data science tools (e.g., TensorFlow, scikit-learn).
• Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration skills with the ability to translate technical concepts to non-technical stakeholders.
• Ability to manage multiple projects and prioritize tasks in a fast-paced environment.