Data Analytics Engineer, Gecko Robotics

• Exceptional organizational and time management skills
• Adaptable, with strong problem-solving and critical thinking skills while working in a rapidly changing environment with dynamic objectives and iteration with users
• Demonstrated ability to continuously learn, work independently, and make decisions with minimal supervision
• Excellent written and verbal communication skills with the ability to collaborate effectively with both technical and non-technical stakeholders
• Mission-oriented, seeking meaningful work for the betterment of our world
• Bachelor’s degree in fields such as Computer Science, Data Engineering / Science, Mathematics, Software Engineering, Physics or relevant experience
• 3+ years in data engineering, operations, and/or application development roles, solving diverse business problems utilizing data and related analytical methods
• Familiarity with data structures, storage systems, cloud infrastructure, front-end frameworks, and other technical tools
• Proficiency with common data engineering and analysis languages (e.g., Python, SQL, Spark, Scala, Java, etc)
• Expertise in ETL design and operations, DevOps and CI/CD, and Data governance

Desirable

• The Data Engineer - Internal Systems is responsible for enabling our organization to harmonize Gecko’s internal data to make business-critical decisions. This is the first internal role of this kind, and will have high ownership in guiding internal decisions regarding data.
• You will be a primary interface and thought-partner delivering end-to-end solutions with key stakeholders across all internal teams, including Engineering, Operations, Manufacturing & Supply, Sales, Finance, People, and Recruiting
• Integrate disparate data systems to create unified data views by designing, developing, and maintaining scalable data pipelines and ETL processes
• Collaborate with internal teams to understand their data needs and requirements
• Produce analyses and reporting while building toward self-service enablement
• Ensure the effective operation and uptime of data infrastructure
• Implement solutions for robust data collection from various internal and external sources
• Monitor and ensure the accuracy, consistency, and security of data
• Perform data cleansing and validation to maintain high data quality
• Implement and advocate for innovative data engineering practices and tools