Data Solutions Analyst

WilioT Ltd; San Francisco (CA); Hybrid; USD 90,000 - 120,000; Full time

Job summary

Wiliot is seeking a Data Solutions Analyst to join our delivery teams and partner with customers on real-world IoT deployments.

You will monitor, analyze, and improve data quality and performance across customer environments, work with cross-functional Scrum teams, and translate data into actionable insights that drive deployment success and business impact. This customer-facing role requires strong communication and analytical skills.

Qualifications

• Bachelor's degree in Math, CS, data science/engineering or equivalent analytical degree.
• 3–5+ years of experience in data analysis, technical customer-facing roles, or similar.
• Architecture experience in big data, data warehousing, operational analytics and integration.
• Strong Python skills.
• Experience with SPARK strongly preferred.
• Visualization tools experience including UI design (Plotly, Tableau, PowerBI, Grafana)
• Understanding of statistical analysis and relational database structures (SQL,Influxdb a plus)
• Strong analytical and quantitative problem-solving abilities
• Excellent interpersonal and communication skills
• Ability to be self-sufficient and execute quickly when given autonomy
• Experience with IoT data streams and business context a plus
• Flexibleteam playerwho will thrive in a dynamic, constantly evolving environment

Responsibilities

• Work closely with customers as part of ongoing projects and deployments.
• Monitor real-time data streams and system performance across customer environments.
• Analyze data to identify trends, gaps, and anomalies in performance and data quality.
• Investigate issues and perform root cause analysis (e.g. data collection issues, tag placement, configuration gaps, integration issues).
• Translate data into clear, actionable insights for both customers and internal teams.
• Build dashboards and visualizations to communicate system performance and business impact.
• Partner with FDE, Product, and Engineering teams to improve solutions and close gaps.
• Escalate product or data issues and collaborate with internal teams to drive resolution.
• Guide customers and field teams on best practices to improve deployment performance and data quality.

Skills

Python

SQL

Data analysis

Communication

Analytical thinking

IoT data

Education

Bachelor's degree in Math, CS, data science/engineering or equivalent analytical degree

Tools

Spark

Plotly

Tableau

PowerBI

Grafana

InfluxDB

Job description

Data Solutions Analyst

Dallas

Wiliot was founded by the team that invented one of the technologies at the heart of 5G. Their next vision was to develop an IoT sticker, a computing element that can power itself by harvesting radio frequency energy, bringing connectivity and intelligence to everyday products and packaging, things previously disconnect from the IoT. This revolutionary mixture of cloud and semiconductor technology is being used by some of the world’s largest consumer, retail, food and pharmaceutical companies to change the way we make, distribute, sell, use and recycle products.

Our investors include Softbank, Amazon, Alibaba, Verizon, NTT DoCoMo, Qualcomm and PepsiCo.

We are growing fast and need people that want to be part of the journey, commercializing Sensing as a Service and enabling “Intelligence for Everyday Thing”.

About the Role

We are looking for a Data Solutions Team Lead to join our delivery teams and work closely with customers on real-world IoT deployments.

In this role, you will be responsible for monitoring, analyzing, and improving the quality and performance of data generated from customer environments. You will work as part of cross-functional Scrum teams, partnering with customers, product, and engineering to ensure successful deployments and meaningful data outcomes.

This is a highly customer-facing, hands-on role that sits at the intersection of data, operations, and product.

Responsibilities

• Work closely with customers as part of ongoing projects and deployments
• Monitor real-time data streams and system performance across customer environments
• Analyze data to identify trends, gaps, and anomalies in performance and data quality
• Investigate issues and perform root cause analysis (e.g. data collection issues, tag placement, configuration gaps, integration issues)
• Translate data into clear, actionable insights for both customers and internal teams
• Build dashboards and visualizations to communicate system performance and business impact
• Partner with FDE, Product, and Engineering teams to improve solutions and close gaps
• Escalate product or data issues and collaborate with internal teams to drive resolution
• Guide customers and field teams on best practices to improve deployment performance and data quality

Requirements

• Bachelor's degree in Math, CS, data science/engineering or equivalent analytical degree
• 3–5+ years of experience in data analysis, technical customer-facing roles, or similar
• Architecture experience in big data, data warehousing, operational analytics and integration.
• Optimize the performance of big data systems to design and implement efficient analytics algorithms.
• Strong Python skills
• Experience with SPARK strongly preferred.
• Visualization tools experience including UI design (Plotly, Tableau, PowerBI, Grafana)
• Understanding of statistical analysis and relational database structures (SQL,Influxdb a plus)
• Strong analytical and quantitative problem-solving abilities
• Excellent interpersonal and communication skills
• Ability to be self-sufficient and execute quickly when given autonomy
• Experience with IoT data streams and business context a plus
• Flexibleteam playerwho will thrive in a dynamic, constantly evolving environment

#LI-Hybrid