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Added 3 mins ago
Director & Human Resources Business Partner | Great West
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Neoflow

Data Engineer

Calgary, AB, Canada

Pay: Pay: CA$100,000 to CA$140,000 per year
Job type: Full-time
Apply by: Oct 31, 2026
Posting language: English
Posted: Oct 1, 2026

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Original job description

Neoflow | Calgary or Toronto, hybrid

Pay: CA$100,000 to CA$140,000 per year

Job type: Full-time, Monday to Friday

Office days: Mondays, usually

Data pipelines for actual pipelines

A lot of data work ends in a dashboard. This job ends at the border.

Every day, millions of barrels of crude oil move from Canada into the United States by pipeline, and every shipment raises the same questions. Where did it come from? Who owned it along the way? What’s actually in it? Neoflow answers them with verifiable data. You’ll build the pipelines that make that data trustworthy, turning raw records from shippers, pipeline operators, and refiners into something U.S. Customs and Border Protection (CBP) can rely on.

What Neoflow does

Our platform gives crude oil and natural gas shipments a verifiable digital passport. It records where the product came from, who held it, and what happened along the way, then shares that record with CBP, customs brokers, and refiners in real time.

This isn’t a slide deck. We built it with CBP and the U.S. Department of Homeland Security, and it’s in commercial operation today. Since July 2026, it’s also been part of a live CBP pipeline test under the National Customs Automation Program. We’re SOC 2 Type 2 certified, headquartered in Calgary, and growing in Canada and the United States.

What you’ll work on

A big part of how data moves through Neoflow will be yours, from the moment it lands to the moment someone at the border relies on it.

You’ll build batch and streaming pipelines for shipment data: delivery tickets, batch measurements, custody and ownership events, and delivery schedules.
Messy data comes with the territory, so deduplication, entity resolution, schema changes, and quality checks are a big part of the job. (Cubic metres on one side of the border, barrels on the other. One shipper, three spellings.)
Different parties report on the same shipment, and they don’t always agree. You’ll build the checks that catch quantities that don’t match or custody that skips a step.
Where LLMs help, you’ll run them in production properly: inputs, orchestration, retries, timeouts, and cost, with a person reviewing the result when the model isn’t confident or the stakes are high.
Every generated result links back to its source records. Traceability is literally our product, so our own pipelines had better have it too.
And you’ll keep an eye on all of it in production, with monitoring, evaluation, drift detection, and a safe way to roll back when something goes sideways.

Who you’ll work with

Day to day, you’ll work directly with Patrick Mandic, our CTO, and Mahmoud Alkhraishi, our Director of Engineering. It’s a tight-knit team with no layers in between, so you’ll take work from idea to production and have a real say in what we build next.

About you

Most of this should sound familiar:

You’ve spent around 5 years building and running data pipelines in production, on Snowflake, BigQuery, Redshift, Databricks, or something like them. You know data modeling, ETL and ELT, and how to make slow things fast.
Python and SQL are home turf, and TypeScript is a plus if you have it.
Data quality is part of how you build: tests, contracts, anomaly checks, reconciliation.
You’ve taken an LLM-powered workflow to production and dealt with what happens when the model gets it wrong.
Security, privacy, and audit trails matter to you, because our data ends up in front of CBP and has to hold up.

Also nice, not required: AWS, Docker and Kubernetes, Terraform, Airflow or Dagster, Kafka, and vector search or evaluation tooling. Bonus points for experience with energy, logistics, or customs data, or with W3C Verifiable Credentials and EPCIS. Never seen a pipeline delivery ticket? That’s fine. We’ll teach you.

Don’t match every line? Apply anyway. We care more about how you think than a perfect checklist.

What we offer

Extended health, dental, and vision care
Life and disability insurance
Paid time off and a flexible schedule
Company events and casual dress

Sound like you?

Apply with your resume and a short answer to one question: tell us about a data pipeline you’re proud of, or one that broke and what you changed afterwards. A few sentences is plenty.

If you need an accommodation at any stage of hiring, just ask and we’ll work it out with you.

This posting is for an existing vacancy.

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More about this job

Responsibilities

Build and operate batch and streaming pipelines that transform shipment records into reliable, traceable data for customs and industry partners. Implement data quality and reconciliation checks, production LLM workflows with human review, and monitoring, evaluation, drift detection, and rollback safeguards.

Requirements

The role calls for around five years of experience building and operating production data pipelines using a modern data platform, along with strong Python, SQL, data modeling, ETL/ELT, and data quality practices. Candidates should have production experience with LLM-powered workflows and care about security, privacy, and auditability; experience with energy, logistics, customs data, or verifiable credentials is a bonus.

Skills

Data Engineering
Data Pipelines
Python
SQL
Data Modeling
ETL
ELT
Data Quality
LLM Workflows
Entity Resolution
Data Reconciliation
Monitoring
Drift Detection
Security
Audit Trails
TypeScript

Benefits

Extended Health Care
Dental Care
Vision Care
Life Insurance
Disability Insurance
Paid Time Off
Flexible Schedule
Company Events
Casual Dress

Visa sponsorship

Not detected in the job text

Hiring contact

Patrick Mandic

Keywords

Data Engineering
Batch Processing
Streaming Pipelines
Shipment Data
Delivery Tickets
Batch Measurements
Custody Events
Ownership Events
Delivery Schedules
Snowflake
BigQuery
Redshift
Databricks
Python
SQL
TypeScript
ETL
ELT
Data Modeling
Data Quality
Entity Resolution
LLM Orchestration
AWS
Docker
Kubernetes
Terraform
Airflow
Dagster
Kafka
SOC 2 Type 2

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