Full-time · Calgary-based, hybrid or remote · Reports to the CPTO Arolytics helps oil & gas operators cut methane through operational efficiency. AroIQ, turns the SCADA data operators already collect into emission events — each with a measured volume and a likely cause, ranked by what they cost. Our engineering team is small and senior, and the software it ships has real environmental, operational, and regulatory impact for operators across North America.

Several new upstream and midstream customers are onboarding, and the platform is scaling from a handful of sites to hundreds. Our numbers show up in regulatory filings, carbon cost models and operator budgets. We don't ship "close enough." We work with real industrial telemetry: high-volume, gapped and noisy.

Small team, low bureaucracy, and your work ships fast. The product sits where process engineering, data science and software meet. You turn product direction into specs and acceptance criteria, accept or reject what the team builds, and run releases with the engineering manager.

Most of our product work now lives in the data layer: how model outputs land in the platform, how events, volumes and costs roll up, and how each customer's data maps into one product. Inside your area you have the authority to decide, and you help shape where the product goes next. You join customer sessions so you hear needs first-hand. what ships after acceptance testing, scope and sequencing within the quarter, what each field in the data contract means, and whether a customer's onboarded data is accepted. new commitments to customers and changes of direction.

Customer calls become structured signal. Agents process call transcripts into feature requests, decisions and customer notes,



so nothing evaporates. Specs start as drafts, not blank pages. PRDs, technical designs and build prompts are drafted by agents from the evidence, then shaped and decided by a person.

We build working prototypes on real customer data, inside our access controls, and hand them to engineering instead of describing screens in words. Data QA at scale. Claude profiles a new customer export, flags what won't map and drafts the transform.

Acceptance stays human: you own whether the data shows up right. Customer data stays inside our approved environments and access controls, and every prototype, agent and AI tool works within them. Write the spec and acceptance criteria for every build, each with a real data example and the expected values.

Run user acceptance testing and decide what ships. Write release notes the customer-facing team can use. Own data accuracy Keep reference datasets with known-correct totals for each customer, and the regression checks that run against them. data contract at every boundary: customer systems into our data platform, data science outputs into AroIQ, and AroIQ back out to customers.

What each field means, not just where it goes. Accept each new customer's data onboarding. Data Engineering builds the pipeline; you decide whether the data is right: mapping, completeness, and numbers that reconcile.





Work with customers and the team Join customer sessions, capture feedback and turn it into scoped work. Work daily with data scientists, data engineers and emissions analysts. 4+ ) in B2B Enterprise/SaaS product management, technical product or data roles on data-heavy software. Technical awareness, no software engineering background needed.

You understand how data flows from source to screen, what a data contract guarantees, and at what grain a number is counted. Writing SQL by hand is not required. in oil and gas, emissions or industrial operations: SCADA or process data, GHG quantification, or emissions reporting. Claude or similar) for specs, analysis and QA, and able to judge its output.

Clear writing. A background as a process, facilities or emissions engineer who moved into software or product.

Experience with PostgreSQL, time-series data or data pipelines. Time at an early-stage company. Scaling from a handful of sites to hundreds per customer, with numbers that stay consistent across every view.

One product serving both emissions and operations use cases, without forking the data model. Moving from historical data drops to near-live data from customer systems. A data contract that holds as the number of customers grows.

A project manager who tracks tickets for others. Someone who uses AI as a chat box for the occasional question, rather than as the way the work gets done. Competitive salary and comprehensive advantages.

Daily work with data scientists and emissions specialists who know the domain deeply. A small team where your decisions ship in weeks, not quarters. Calgary-based, with hybrid and remote flexibility. #

📌 Product Manager Remote (m/f/d) (Winnipeg)
🏢 Arolytics
📍 Winnipeg