PivotBio

Data Engineer I - Research Agronomy

Remote
USD 81k - 101k
Python SQL R API
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Description

About Pivot Bio:  

Fueled by an innovative drive and a deep understanding of the soil microbiome, Pivot Bio is pioneering game-changing advances in agriculture. Our products harness the power of naturally occurring microbes to provide nutrients to crops and new sustainable ways for farmers to reduce the usage of fertilizers as they work to help feed the world’s growing population.

Read/Hear more about Pivot Bio on Forbes or PBS News Hour. 

Position: Data Engineer I, Research Agronomy

Pivot Bio is rapidly expanding its field trial network and growing its customer base, producing new sources of data for analysis. This data needs to be curated and maintained in coordination with our customer-facing agronomy team. The Data Engineer, Research Agronomy will be a member of the Data Operations team within the Scientific Computing group. This person will interact with the agronomy and data science teams to create and manage the process of data ingestion and schema development for this class of data. They will help coordinate the data collection efforts of the agronomy team, so that fast and insightful analyses can be provided to them. 

 Responsibilities: 

  • Develop, curate, and maintain data and data pipelines for research/product development agronomy including the management of Pivot Bio’s field and customer data 
  • Query, collate, and create ad-hoc reports in a rapid response environment 
  • Help make data visually accessible to non-technical stakeholders through the creation of front-end tools and visualization dashboards  
  • Build relationships with Pivot Bio agronomy team to facilitate quality data acquisition practices where needed 
  • Help develop tools and processes increase efficiency, integrity, and accuracy in data collection for the agronomy team 
  • Travel up to 10% of the time for visits to field trial sites, customer sites 
  • Interact with ARM (Agriculture Research Management) and CropTrak software

Physical Demands:

  • Job will involve mostly (95%) office work with occasional (5%) time spent in the field to understand processes
  • Repeating motions that may include the wrists, hands, or fingers
  • Sedentary work that primarily involves sitting/standing
  • Communicating with others to exchange information

 Qualifications and Experience: 

  • Bachelors or higher degree in STEM with 2+ years of relevant experience in data stewardship and research or production agriculture 
  • Foundational skills with Python and SQL (R is a plus) with demonstrated experience (e.g. coursework or Github portfolio), experience with REST APIs, and manipulating databases in a user-oriented environment 
  • Experience navigating data ecosystems (e.g. databases, data lakes) 
  • Familiarity with data management infrastructure such as Databricks, Snowflake, or other pipeline management tools  
  • Strong attention to detail and orientation to process 
  • Great communication skills 

*Must be authorized to work in the United States *

 What will set you apart:

  • Agronomy-related specialty with demonstrated working experience
  • Experience with field-based research
  • Experience working with Tableau, Dash, Spotfire (or similar data visualization tools) generating visualizations and dashboards 
  • Experience designing and implementing data quality metrics
  • Demonstratable experience with mentorship

What we offer: 

  • Competitive package in a disruptive startup 
  • Stock options 
  • Health/Dental/Vision insurance with employer-paid premiums 
  • Life, Short-Term and Long-Term Disability policies 
  • Employee Assistance Program with free referrals and discounts 
  • 401(k) plan, 3% Match 
  • Commuter benefits 
  • Annual Training & Development support 
  • Flexible vacation policy with a generous holiday schedule 
  • Exciting opportunity to work with a talented and fun team 

Hiring Compensation Range: $81,170 - $101,463

All remote positions and those not located in our Berkeley, Hayward or Boston locations are paid based on National Benchmark data.  Following employment, growth beyond the hiring range is possible based on performance.

 

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