Senior Data Engineer: Industrial Data Pipelines & AI

Greenhouse Software, Inc.; Georgia; Hybrid; USD 120,000 - 160,000; Full time

Benefits offered by this job

Competitive compensation

401(k) with employer matching

Health, dental, vision & disability

Job summary

Cognite in Houston, TX is seeking a Senior Data Engineer to design, develop and implement data infrastructure and pipelines that connect data from multiple sources, supporting reliable analytics and data-driven decisions.

This hybrid role requires 7+ years in data-intensive environments, experience in in Oil & Gas or Manufacturing, and travel to client sites. You will work with Python, Spark, SQL, Kafka, and Docker to deliver scalable solutions.

Qualifications

• 7+ years of experience in a Data intensive role
• Experience in O&G and/or Manufacturing is required
• BS or MS degree in computer science or related field
• Loves to code, passion for coding, and enjoys sharing that knowledge with others
• Strong understanding of data analysis or data science
• Experience working with data technologies, such as: ETL, SQL, Python
• Ability to travel onsite to meet with and engage with clients -- we don’t build solutions in isolation.

Responsibilities

• Partner with Solution Architects to understand client requirements and define queries with subject matter experts
• Develop custom extractors using backend technologies and languages i.e Python, Spark, Rest APIs
• Customize existing extractors i.e. database extractor using SQL, event streaming using Kafka and deploy using Docker
• Create custom data models for data discovery, mapping, and cleansing
• Collaborate with product development to turn customer needs into potential product offerings
• Prototype data visualization and dashboards

Skills

Python

Spark

SQL

ETL

Data analysis

Data science

Rest APIs

Kafka

Docker

Education

BS in Computer Science

MS in Computer Science

Tools

Docker

Kafka

Job description

Cognite in Houston, TX is seeking a Senior Data Engineer to design, develop and implement data infrastructure and pipelines that connect data from multiple sources, supporting reliable analytics and data-driven decisions.

This hybrid role requires 7+ years in data-intensive environments, experience in in Oil & Gas or Manufacturing, and travel to client sites. You will work with Python, Spark, SQL, Kafka, and Docker to deliver scalable solutions.