Data Engineer with a Focus on Analytical Research

WINT develops IoT hardware and software water-management solutions for the real-estate and industrial sectors.

The devices are installed in buildings – such as the Empire State Building and on construction sites. The system monitors usage patterns and uses Machine Learning, signal processing and statistical analysis techniques to detect anomalies and prevent leaks by shutting off water. Our customer prevents massive damage to facilities – which could reach millions of dollars per incident and save 20%-25% of their ongoing water consumption.

WINT was named in Fast Company's Annual List of the World's Most Innovative Companies for 2020 and has won numerous other awards.

We are seeking a Data Engineer who combines data engineering expertise with a proven record in research. This role demands a keen eye for understanding new datasets, tackling technical challenges, and venturing into unfamiliar domain areas. Crucially, this role will play a pivotal part in scaling our data infrastructure to support advanced anomaly detection and handle increasing volumes of IoT data. 

1. Data Engineering, Analysis, and Anomaly Detection: 

• Bring 3-5 years of experience in data engineering, focusing on constructing and optimizing data pipelines and datasets. 
• Conduct exploratory and quantitative data analysis, handling both large and small datasets to derive insights. 
• Engage in the development and refinement of algorithms for anomaly detection, leveraging experience with IoT/Industry 4.0 data and its unique challenges. 

2. Research and Data Acquisition: 

• Showcase a history of independent research to unravel complex data structures and domain areas, particularly in ambiguous situations. 
• Extract, integrate, and analyze IoT data streams to understand the workings of industrial devices. 

3. Data Processing and Scalability: 

• Clean, transform, and structure data, customizing data processing to align with client-specific needs and the nuances of IoT data streams. 
• Focus on scaling data pipelines to accommodate growing data demands and complexity, ensuring robustness and efficiency in data handling. 

• Industry Experience: At least 3-5 years in data engineering roles, with a preference for experience in IoT or industrial sectors.
• Analytical Research: A strong track record in independent research for technical problem-solving and domain-specific data understanding.
• Technical Proficiency: Advanced skills in Python programming, with Java familiarity being advantageous.
• Proficiency in data pipeline tools like Apache Kafka, Apache Beam, along with container orchestration tools such as Kubernetes for scaling applications, and cloud environments like AWS for managing large-scale data infrastructure.
• Expertise in SQL and other querying languages.
• IoT and Industry 4.0 Knowledge: Competence in understanding and researching complex IoT data streams.
• Interdisciplinary Collaboration: Proven ability to work collaboratively across diverse teams.
•