René Pretorius

Product and Data Platform Leader

Fuquay-Varina, NC

Summary

Player-coach who turns messy farm and commercial data into products operators will act on. I stood up GIS and data-product functions, managed the team that generated most of a company’s revenue, set the performance bar, and defined how the function operated — and now personally own the data platforms those products run on, writing the specs that define what a customer is, what a metric means, and what the platform owes a new farm so we do not build one-offs. I bridge equipment and ERP systems into living products. Daily work is agentic: I write the spec, direct agents on the implementation, and verify against live farm data and regression harnesses so quality holds when the leverage is the spec, not the diff.

Skills

Product: Discovery · Scoping & specs · Roadmapping · Metric & grain definition · Agentic / spec-driven delivery · Verification harnesses · Prioritization
Platforms: Data products & APIs · Warehouse contracts · Farm onboarding without one-offs · Equipment / ERP integrations · QC & lineage
Data & cloud: Python · SQL · GCP (BigQuery, Cloud Run, GCS, Pub/Sub) · AWS (Athena, Glue, S3, Lambda) · PostgreSQL · GeoPandas · Looker
Farm systems: ArcGIS Pro / Online · John Deere Operations Center · FME · ESRI Dashboards · GitLab CI · Jira · Confluence

Experience

Lead Data and Platform Engineer — GROWERS

Feb 2026 – Present

Personally own the farm-operations data platform: replace a broken desktop GIS workflow with a production pipeline that turns planting and harvest equipment files into trusted field records. Validated 100% against known-correct historical cleaning output across 12 real datasets (4 growers, 4 crop types, planting and harvest; ~27M+ raw rows), plus an end-to-end stress test.
Ship that platform through agentic development — plan-mode specs before code, agents on the implementation, then verification harnesses against real grower files and historical cleaning output — so a wrong step fails a test, not a farm.
Write the contracts so a new grower is not a one-off build — from equipment intake and field readiness through quality gates, cleaning, and replant detection — and bridge a legacy OEM system (John Deere Operations Center) into the same platform. Incremental exports raised live success from ~44% to ~93% of terminal operations; a two-track plan kept existing farms on the working path while unblocking new-farm onboarding. Completing that auto-pipeline is what makes the next 40 full-season growers (~4.6B raw points through the system) a ~1-month onboarding, which was not possible on the prior path.
Scoped a retailer-facing loyalty and customer-insights product against the existing manufacturer-facing analytics product: unique-customer definition, engagement and churn, per-customer points and expiration, salesperson-view limits, and the warehouse views the product needs. Caught a churn model keyed on the wrong account grain before it shipped, and mapped dashboard plus LLM-backed surfaces onto the data platform so engineering did not guess the contracts.
Run the loyalty and rewards data platform as a product for internal customers (engineering, agronomy, dashboards): tier history and purchase-category logic for loyalty reporting, per-customer points balance, and a production fix so a failure in one data product no longer aborts independent builds of others. Translate “product bugs” (missed soft-deletes, manufacturer attribution, customer-spend identity vs. pooled loyalty-tier accounting) into platform contracts and written tradeoffs.
Partner with farm intelligence and ops owners on soil-lab ingestion and field-boundary update rules. Catch non-obvious data-integrity failures before they become product bugs — for example an automation that silently fragmented multi-polygon fields when boundaries were updated. Built a QC framework that cut QC load ~80%; keep two recently merged company warehouses aligned so farm intelligence and loyalty products share one set of numbers. The result is a three-to-four person team carrying more work at higher quality as the company scales, instead of matching load with headcount.

Data Operations Manager — GROWERS

Oct 2022 – Feb 2026

Stood up the data-products function that generated ~60% of company revenue: hired and coached a small team, set the performance bar, gave ongoing feedback and growth, and retained everyone (zero turnover). Player-coach: still in the work, while defining how the team planned, delivered, and raised quality.
Replaced 95% of printed customer reports with living decision-support products for crop farming and agricultural retail — the path that let customers act on data instead of waiting on ops — improving retention and cutting operational cost.
Owned discovery, scoping, and delivery with engineering, marketing, and support: wrote what each product owed the customer, ran concurrent roadmaps against near-term ship dates and longer-term platform strategy, and used knowledge-graph lineage so stakeholders shared one definition of the numbers.
Automated nearly 90% of geospatial operations and removed more than 60% of manual pipeline work — enough to process ~2.9B raw John Deere points across 33 growers with a three-to-four person team, at higher quality, while headcount stayed nearly flat.
Delivered retailer-facing insights for customer base, loyalty-program strategy, and retention — translating complex transactional and geospatial data into justified decisions sales and agronomy teams would actually use.

Senior GIS Specialist — GROWERS

Sep 2020 – Oct 2022

Designed geospatial decision-support for agricultural and commercial initiatives — tools stakeholders used to decide, not static maps.
Automated data-management workflows so products were repeatable; ran documentation, training, and retrospectives so other teams could operate them without the original owner in the room.
Worked discovery with cross-functional partners to refine products against client need and technical constraint before committing engineering time.

Manager, GIS & Environmental — GreenGo Energy US, Inc.

Jul 2017 – Sep 2020

Built the GIS and environmental department from scratch — role definitions, workflows, and standards — rather than inheriting one, so a renewable-energy developer could site projects and speak to investors from one consistent practice.
Shipped an ESRI-based field platform so teams could capture, analyze, and assess project feasibility and profitability, and so leadership could report those decisions to investors. Added web apps that made project status visible across departments and usable in investor communications.
Automated mapping and analysis with Python so a small team could carry a large renewable-energy development load — high project volume, investor timelines — and still deliver on time. Wrote training and ran sessions for online and mobile users.
Directed environmental workstreams, pre-construction surveys, and permitting with consultants and subcontractors so projects stayed on regulatory, schedule, and investor requirements.