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Data Engineer

  • Remote, Canada

Remote

Contract

This opening has closed.

The original listing is kept below for reference.

Job details

Job type
Contract
Workplace
Remote
Experience
5+ years of senior-level data engineering experience with a proven track record of designing data architecture, data lakes/warehouses, and complex ETL/ELT pipelines.
Posting language
English
Posted

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Original job description

Archived listing. The details below describe a past opening.

About Future Works

Future Works is a US-focused, AI-native professional services firm building operational AI and data systems. Our foundation beliefs are simple: optimization lowers need for resources, which increases sustainability and resilience. We are a team of "Time Benders" on a mission to collapse timelines to operational transformation of high footprint companies in energy, real estate, data and beyond. Together, we master velocity.

We achieve our mission by building flawless, AI-powered systems. Our technology is already far more advanced than that of boutique services firms, but we are only getting started and the road from here leads to becoming world's best Service-as-Software company. Regardless of the specific role, our ideal candidate will always have a keen interest in building symbiotic human-AI systems both individually and for teams; high energy, high agency and a certain passion for bending time.

The role

As the Data Engineer, you will build the critical data foundation that makes this transformation possible. You will be accountable for extracting and unifying highly fragmented historical logistics data to power advanced AI simulations. You will work closely with Solutions Architects, Business Analysts, and Full Stack Engineers to establish a secure environment and a canonical schema that translates raw supply chain data into insights that drive speed, efficiency and fiscal gain.

Key Responsibilities

  • Data Ingestion & Structuring: Lead the extraction, ingestion, and harmonization of historical freight, order, inventory, and complex carrier rate card data from diverse legacy sources.

  • Schema Design: Define "Minimum Viable Attributes" and architect a unified, canonical data schema that normalizes client data for downstream consumption.

  • Pipeline Development: Build robust, reusable ETL/ELT pipelines to facilitate rapid and structured analysis in a highly regulated environment.

  • Quality Assurance for Modelling: Ensure data quality, completeness, and readiness are sufficient to train predictive machine learning models and run optimization simulations.

  • Infrastructure Collaboration: Work alongside the Solutions Architect to stand up and operate within a secure, single-tenant sandbox environment ensuring strict data isolation.

  • Hypothesis Validation: Support the Operations Strategy team by providing the necessary data structures to decompose current allocation logic, enabling the identification of wrong-node, mode-mix, and escalation drivers.

What We’re Looking For

Required Skills and Experience

  • 5+ years of senior-level data engineering experience with a proven track record of designing data architecture, data lakes/warehouses, and complex ETL/ELT pipelines.

  • Technical Mastery: Deep proficiency in Python, advanced SQL, and modern data processing libraries

  • Cloud Expertise: Hands-on experience working within cloud environments to deploy secure, high-performance data infrastructure (e.g., PostgreSQL).

  • Domain Knowledge: Previous experience working with supply chain, logistics, or ERP data (shipment histories, inventory levels, freight billing) is highly preferred.

  • Agile Execution: Ability to thrive in rapid, hypothesis-driven sprint cycles (12-week models) where the focus is on validation experiments rather than traditional, slow IT delivery.

  • AI-Native Workflow: Comfort utilizing LLM code assistants (e.g., Cursor, Copilot) and agentic engineering to multiply your productivity and enhance code quality.

Our Culture & Benefits

We believe that breakthrough results are driven by breakthrough experiences. Our culture is built on a foundation of freedom, high performance, and our seven core values.

Our Core Values

  • AI native - We use AI as a natural extension of our abilities to deliver faster, smarter, and better work.

  • Delivering joy - We underpromise and overdeliver, creating delight for our clients and our team.

  • Smooth & fast - We believe speed is the result of precision, flawless systems, and calm execution - not frantic effort.

  • Selfless - We proactively make work easier for others and measure our success by the success of the team.

  • Candid - We are direct, honest, and clear with each other, believing that transparent feedback is a gift.

  • Pursuing excellence - We are obsessed with quality and empower each other to break through boundaries and set new standards.

  • Ever evolving - We are relentlessly curious and improve every single week, sharing our learnings openly to elevate the entire organization.

Benefits & Perks

  • Work from anywhere, forever - We are a fully remote and global team. We trust you to manage your time and energy to deliver exceptional results.

  • Connect deeply - We gather for immersive, all-expenses-paid company retreats in unique locations to connect, learn, and grow together.

  • Share in the upside - A competitive compensation package including equity, bonuses, substantial participation in company profits with a clear growth path to C-Level leadership based on performance.

More about this job

Responsibilities

The Data Engineering Lead will be responsible for building the critical data foundation by extracting and unifying fragmented historical logistics data to power advanced AI simulations. Key duties include leading data ingestion, architecting a canonical data schema, and building robust ETL/ELT pipelines.

Requirements

Candidates must possess over 5 years of senior-level data engineering experience, demonstrating mastery in Python, advanced SQL, and modern data processing libraries, along with hands-on cloud infrastructure deployment experience. Prior domain knowledge in supply chain or logistics data is highly preferred, as is the ability to execute within rapid, hypothesis-driven sprint cycles.

Skills

  • Python
  • SQL
  • Data Ingestion
  • Schema Design
  • ETL/ELT Pipelines
  • Data Quality Assurance
  • Cloud Infrastructure
  • PostgreSQL
  • Supply Chain Data
  • Logistics Data
  • ERP Data
  • Agile
  • LLM Code Assistants
  • Agentic Engineering

Benefits

  • Work from anywhere, forever
  • Company retreats

Remote locations

  • Canada

Remote locations (standardized)

  • Canada

Visa sponsorship

Not detected in the job text

Categories

  • Data & Analytics
  • Engineering
  • Software
  • Logistics
  • Management & Leadership

Keywords

  • Data Engineering
  • Data Foundation
  • Logistics Data
  • AI Simulations
  • Data Unification
  • Canonical Schema
  • Supply Chain Data
  • Data Ingestion
  • ETL
  • ELT
  • Data Warehouses
  • Data Lakes
  • Python
  • SQL
  • PostgreSQL
  • Cloud Environments
  • Data Quality
  • Machine Learning Models
  • Optimization Simulations
  • Secure Environment
  • Agile
  • Sprint Cycles
  • LLM Code Assistants
  • Agentic Engineering
  • Freight Data
  • Carrier Rate Card Data
  • Legacy Sources

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