Analytics Engineer: Data Pipelines & Predictive Modeling

Socket.dev; Shelton (CT); On-site; USD 100,000 - 150,000; Full time

Job summary

Socket.dev seeks an Analytics Engineer to design and maintain data pipelines, models, and analytics tools. You will apply data science techniques to build predictive models that impact manufacturing, product development, and sales strategies.

You will collaborate with engineers, product managers, and business stakeholders to define KPIs, dashboards, and reporting tools, while advancing data infrastructure and governance across the organization.

Qualifications

• Bachelor’s degree in a related field; Master’s preferred.
• 2+ years in data engineering, data science, or similar.
• Strong SQL and Python for data manipulation and analysis.
• Experience with ETL, data warehousing, cloud platforms, and ML frameworks.
• Strong data modeling, data architecture, and BI tooling knowledge.
• Familiarity with big data tech (Hadoop, Spark) is a plus.
• Experience with ML algorithms and predictive modeling.
• Excellent problem-solving and communication skills.

Responsibilities

• Design, build, and maintain scalable data pipelines for large data volumes.
• Develop data models and KPIs; create dashboards and reports.
• Apply statistical methods and data science techniques to improve manufacturing, product development, and sales.
• Develop predictive models and ML algorithms; integrate into products.
• Collaborate with engineers and product teams to deploy data science solutions.
• Provide training and support on data tools and analytics best practices.

Skills

SQL

Python

Data Engineering

Data Science

Machine Learning

Communication

Collaboration

Education

Bachelor’s in Computer Science or Data Science

Master’s degree preferred

Tools

ETL tools

Power BI/Tableau

AWS/Azure/GCP

Spark

Grafana

Job description

Socket.dev seeks an Analytics Engineer to design and maintain data pipelines, models, and analytics tools. You will apply data science techniques to build predictive models that impact manufacturing, product development, and sales strategies.

You will collaborate with engineers, product managers, and business stakeholders to define KPIs, dashboards, and reporting tools, while advancing data infrastructure and governance across the organization.