We are looking for a Senior Data & Automation Engineer to join our Product Analytics team and drive data-driven solutions, automation, and analytics tools across our manufacturing operations. If you're passionate about building impactful systems, have strong software engineering skills combined with data analytics expertise, and thrive in a collaborative environment, we'd love to hear from you!

What you'll be doing:

• Design, develop, and deploy automation solutions, dashboards, and analytical tools using Python Build and maintain data pipelines and workflows to improve data integrity and streamline data flows across systems

• Participate as a data analyst and technical contributor in cross-functional task forces addressing critical manufacturing and quality challenges

• Perform system characterizations and collaborate with internal teams to identify opportunities for optimization and deliver custom solutions

• Develop machine learning and AI-driven solutions for anomaly detection, quality control, and predictive analytics

• Present technical insights and recommendations to stakeholders and drive data-informed decision-making

What we need to see:

• BSc in Computer Science, Engineering, Information Systems, or relevant field

• 5+ years of hands-on software development and data analysis experience

• Strong proficiency in Python with experience in data science libraries (Pandas, NumPy, SciPy, Matplotlib)

• Experience with machine learning frameworks (Scikit-learn, XGBoost) and AI/ML platforms

• Proven track record of building automation tools, scripts, and production-ready software solutions

• Experience with SQL and working with large-scale datasets Proficiency with version control systems (Git)

• Experience in dashboard development and data visualization tools (Streamlit, Plotly, Dash, Power BI or similar)

• Excellent communication and collaboration skills with ability to work across multiple teams Self-driven with a problem-solving mindset and ability to translate business needs into technical solutions

Ways to stand out from the crowd:

• Background in manufacturing, yield engineering, or product engineering environments

• Experience deploying ML models in production environments

• Familiarity with CI/CD practices and automated testing