We are ShipMonk, and we provide logistics services in order fulfillment. Our main business is in the USA, but our modern platform is built by the Product Development team in Prague.

Here at ShipMonk, we process up to 100,000 orders per day in our peak season. Our book of business has more than 1,500 clients which are small and medium e-shops, mostly based in the US. We offer the ShipMonk platform as the solution for the whole process.  It covers everything from stocking the items to shipping the ready packages to all corners of the world!

🎯 1. ROLE MISSION

We seek a High-Execution Data Engineer to be the lead architect and primary builder of the Merchant Data Catalogue (MDC). This "Builder-Architect" role requires designing, coding, building, and maintaining the infrastructure to transform complex 3PL logistics data into a single, standardized, client-ready data product. Moving beyond fragmented backend data, you will model it into a clean, unified "Merchant-Standard" format. This standardized data directly enables customers to easily calculate and output key e-commerce KPIs, such as drilling down on a 15% shipping cost increase. The MDC is critical as the foundation for our AI insights platform and all future data tooling for our thousands of merchants.

🏗️ 2. THE HANDS-ON CORE RESPONSIBILITIES

• End-to-End Development: Directly build, test, and deploy the ETL/ELT pipelines that feed the Merchant Data Catalogue.
• MDC Management & Oversight: Take full ownership of the MDC lifecycle—from schema design to ongoing performance tuning and maintenance.
• Standardization & Modeling: Get hands-on with SQL and Python to model fragmented backend data into a clean, unified "Merchant-Standard" format.
• Data Contract Enforcement: Code and implement automated checks (Data Contracts) to ensure backend changes never break the client-facing data layer.
• Maintenance & Support: Proactively monitor the health of the MDC. You are the first line of defense for troubleshooting data discrepancies or performance lags.
• Tooling & Automation: Develop internal tooling to automate documentation and data quality reporting for our merchants.
• Data Mining & Insight Modeling: Identify business problems (e.g., "Are you putting inventory in the wrong warehouse?") and construct the underlying data models within the MDC to provide actionable answers via our tooling and customer interfaces.

🛠️ 3. SKILLS & TECHNICAL REQUIREMENTS

• Hands-on Engineering: Expert-level proficiency in Python and SQL. You should be comfortable refactoring complex queries and building scalable data apps.
• Modern Data Stack: Practical experience with dbt, Airflow, Snowflake, and CI/CD workflows for data.
• Data Architecture: Strong ability to design Star Schemas and wide-table formats specifically for high-concurrency client access.
• Reliability Engineering: Experience with data testing frameworks (e.g., Great Expectations, dbt-tests) to ensure "Standard & Robust" delivery.
• Documentation: Ability to write clean, developer-facing and client-facing documentation (Data Dictionaries).

🏆 4. KEY RESULTS (What Success Looks Like)

• KR 1 (Reliability): Achieve 99.9% uptime and delivery of the MDC, meeting all client-facing Data SLAs.
• KR 2 (Business Value/Upsell): Enable the development of analytics features, AI insights, and drill-down dashboards that are 100% based on the Merchant Data Catalog, directly contributing to upsell and technology revenue.
• KR 3 (Insight Foundation): Successfully construct the underlying data models within the MDC to support three high-leverage 2026 Strategic Problems (e.g., Inventory Placement, B2B Planning Accuracy).
• KR 4 (Data Quality/Trust): Implement and enforce Data Contracts for 100% of core client-facing data fields, resulting in a 50% decrease in Merchant Success Manager (MSM) escalations related to data discrepancies.
• KR 5 (Customer Insight Loop): Implement a formal feedback loop to capture and translate merchant/business-user feedback into 3 major quarterly data model improvements within the MDC.
• KR 6 (Internal Adoption): Achieve 90% adoption of all new MDC-based insight models by Merchant Success Managers (MSMs) for weekly client consultations, solidifying the MDC as the trusted single source of truth.

📈 5. DESIRED EXPERIENCE

• 4+ years of hands-on experience in Data Engineering or Backend Engineering.
• Proven track record of building data products from scratch—not just maintaining existing ones.
• Experience working in a 3PL, Logistics, or Fintech environment where data accuracy is mission-critical.
• A "lead-by-doing" mentality: you are as comfortable in a high-level design sprint as you are in a deep-dive debugging session.
• Experience working directly with business users and leveraging customer feedback to drive iterative improvements in data models and products.

🚀 JOIN THE SHIPMONK CREW

We are looking for a highly business-focused Data Engineer who will act as a Data Product Manager for the Merchant Data Catalog. This role's purpose is to accelerate our business by synthesizing user inputs and customer feedback into data models that drive strategic value for our thousands of merchants.

Location: Prague / Hybrid

Data Scientist – Transportation & Logistics Intelligence

About the Role:

ShipMonk has built world-class infrastructure for shipping—our Virtual Carrier Network (VCN), claims systems, and logistics modeling are the rails. Now, we need the engine. We are seeking a Data Scientist – Transportation & Logistics Intelligence to transform our transportation systems to "predictive-first."

In this role, you won’t just be "analyzing data"—you’ll be building the autonomous logic that powers millions of shipments. You are the architect who will replace manual "if/then" rules with real-time, high-margin predictive models. Your mission is to bridge the gap between logistics physics and machine learning, ensuring that manual becomes modeled and reactive becomes predictive.

Desired Experience:

• Education: Master’s or PhD in Data Science, Statistics, Operations Research, or a related quantitative field (or equivalent practical experience).
• Data Core: 4+ years of experience building and deploying predictive models into production environments.
• Data Engineering: Strong proficiency with dbt and SQL within a Snowflake (or BigQuery/Redshift) environment. You should be comfortable collaborating on complex DAGs and version-controlled data pipelines.
• Logistics DNA: Previous experience in transportation, supply chain, or e-commerce logistics is a massive plus. You should understand the nuances of carrier performance, transit latencies, and "last-mile" variables.
• The Stack: Expert-level proficiency in Python and SQL. Experience with machine learning frameworks (e.g., Scikit-learn, XGBoost, PyTorch) and cloud-based data warehouses (Snowflake, BigQuery).
• Business Acumen: Ability to translate complex model outputs into "Margin impact" or "Conversion growth" for stakeholders.

Skills & Responsibilities:

• VCN Optimization (The Margin Engine): Build real-time risk/value models. You’ll build the logic that weighs package value vs. risk of loss to ensure we never overspend on "safe" routes or under-insure "risky" ones.
• Precision EDD (The Conversion Driver): You will develop dynamic Estimated Delivery Date (EDD) models that adjust in real-time based on live network health, weather, and historical carrier latency.
• Predictive "At-Risk" Intelligence: Build the "early warning system" for our warehouse and support teams. You’ll develop models that identify "lost" or delayed packages before a merchant or customer even notices—enabling proactive resolution and automated claims.
• Collaborative Data Preparation: Partner with Engineering to co-author and refine the dbt models and SQL transformations that power your work. You’ll ensure the "preparation layer" is optimized for feature engineering and model training.
• Scalable Modeling: Transform manual logistics workflows into autonomous systems. You’ll be responsible for ensuring our intelligence scales with our global warehouse footprint.
• Cross-functional Collaboration: Partner with Product Managers and Engineering teams to integrate your models directly into the ShipMonk application, moving from "insights on a slide" to "logic in the code."
• A/B Testing & Validation: Design and execute experiments to validate that your models are actually driving the expected increases in margin and delivery reliability.

We are ShipMonk, and we provide logistics services in order fulfillment. Our main business is in the USA, but our modern platform is built by the Product Development team in Prague.

Here at ShipMonk, we process up to 100,000 orders per day in our peak season. Our book of business has more than 1,500 clients, which are small and medium e-shops, mostly based in the US. We offer the ShipMonk platform as the solution for the whole process.  It covers everything from stocking the items to shipping the ready packages to all corners of the world!

The Opportunity

We are looking for a Senior Data Platform Engineer to join our Research & Development team. We recently laid the foundation for our new Data Mart and are actively driving the adoption of a modern Data Platform across the company.

This is not a traditional pipeline-building role. We need an infrastructure-minded engineer to build the paved roads that empower our warehouse, finance, and business development domain teams to independently produce and consume reliable data. You will tackle complex architectural challenges, manage cloud compute costs at scale, and implement production-grade data reliability standards for a logistics network that processes up to 100,000 orders per day.

The Stack

We operate a modern data ecosystem and treat data infrastructure with the same rigor as our core software applications.

• Language: Python
• Storage & Compute: Snowflake
• Transformation & Orchestration: dbt, Airflow, Keboola
• Streaming & Integration: StreamKap, Zapier
• Governance & BI: DataHub, Metabase
• Infrastructure & Security: Terraform, AWS Fargate, Okta

The Impact

We don’t manage your hours; we manage outcomes. We value deep technical expertise paired with a strong product mindset. In this role, you are expected to:

• Platform Enablement: Build reliable, scalable infrastructure that allows domain teams to self-serve. You will shift the company toward decentralized data ownership (Data Mesh concepts) by providing the right tooling and architecture.
• Data Reliability Engineering (DRE): You genuinely care about data integrity. You will introduce rigorous Data Quality standards and SLO-based alerting systems to treat data freshness and accuracy as a high-availability production asset.
• FinOps & Scale: As our data volume and velocity increase, you will promote cost awareness and actively optimize our Snowflake compute, storage, and pipeline architectures.
• Strategic Migration: Guide the architectural transition by assisting data producers and consumers in migrating legacy data flows to our new, scalable Data Platform.
• Technical Ownership: Leverage Terraform and AWS Fargate to continuously improve, secure, and automate our underlying data infrastructure.

ShipMonk is a place where your engineering decisions have a visible, immediate impact on how goods move around the world. We are looking for colleagues who are ready to take ownership, challenge the status quo, and "get sh*t done."

Ready to build the platform that moves the physical world? [Apply via our recruiter – No Cover Letter Needed, Just your Profile/GitHub]

We are ShipMonk, and we provide logistics services in order fulfillment. Our main business is in the USA, but our modern platform is built by the Product Development team in Prague.

Here at ShipMonk, we process up to 100,000 orders per day in our peak season. Our book of business has more than 1,500 clients which are small and medium e-shops, mostly based in the US. We offer the ShipMonk platform as the solution for the whole process.  It covers everything from stocking the items to shipping the ready packages to all corners of the world!

We are looking for a skilled PHP Developer to join ShipMonk! This is an exciting opportunity to join our Product Development Team located in Prague. Please take a look at the details below.

Tech Stack:

• PHP 8.5
• Symfony 7
• Docker
• Kubernetes
• Doctrine ORM 3
• RabbitMQ
• MySQL 8
• GraphQL
• Elasticsearch

Our teams:

• Warehouse: optimization and automation of warehouse processes
• Internals: refactoring, tech-debt reduction, and legacy code removal
• Customer features: development of the functions of the existing web environment
• Frontend: TypeScript clients in React, E2E
• DataScience: AI, DWH, data-governance, prediction, and optimization, business intelligence
• QA: acceptance-criteria testing
• DevOps: Infrastructure, Kubernetes, CI/CD management and Cloud platform management
• Technical Product Managers: Asana & project management

What does it look like and what we are proud of:

• The main backend application provides a REST-like API for several types of clients (web, autonomous robots, iOS picker devices, microcomputer packers, automatic conveyors and more).
• We have the rest of the applications and clients in monorepo for easier CI checks, code sharing, etc.
• We have all services completely dockerized for local development. We deploy builds to a hosted Kubernetes cluster in AWS with a single click on the Argo CD several times a day.
• Each MR can be deployed on a separate cluster for one-button testing in the CI, so we don't argue about a test environment.
• We have set up a lot of checks in GitLab CI (PHPStan, PHP_CodeSniffer, PHPUnit, lint, editorconfig-check, migration check, security scans, renovate-bot).
• In addition to static analysis, we also do a two-round review and the operation is also verified by the QA team and E2E cypress tests.
• We have more than 15 000 database integration tests with the thoughtful creation of independent datasets for each test, ie no shared data that breaks forever.
• We directly automate the agreed coding-rules, so we have already written dozens of our own phpstan rules and coding-standard sniffs.
• We think about concurrence and design the application to withstand race conditions, which is not exceptional in a warehouse environment.
• The application is supported by DataDog, Sentry, and Opsgenie.
• Our database has grown to terabyte size, so even the optimization of SQL queries is becoming the daily bread of all of us.
• We deal with HA, failover, and autoscaling, almost no service runs for us only once.
• Having experienced colleagues is our huge advantage.
• We automatically generate documentation of all our REST-like endpoints.
• We open-source some of our best tools and contribute back to the OS community.
• We utilize code coverage.

If you like what we do, and our "story" got you interested, we look forward to seeing your resume, profile, story, or anything else you might have! There are no limits to creativity. Our Recruiter will get back to you as soon as possible. We look forward to hearing from you!

We are ShipMonk, and we provide logistics services in order fulfillment. Our main business is in the USA, but our modern platform is built by the Product Development team in Prague.

Here at ShipMonk, we process up to 100,000 orders per day in our peak season. Our book of business has more than 1,500 clients, which are small and medium e-shops, mostly based in the US. We offer the ShipMonk platform as the solution for the whole process.  It covers everything from stocking the items to shipping the ready packages to all corners of the world!

We are looking for an AI & Data Analyst in Prague to help us build our AI domain from the ground up. This is a pioneering role with full freedom to shape direction. You will drive real business value through initiatives like automated root cause analysis with AI agents. You will design the tools, processes, and projects while working closely with ShipMonk leadership. Join us in Prague and shape the future of how we use AI.

Key responsibilities

• Shape tools, processes, and bring real business value through data, AI and traditional ML.
• Take full ownership – dig in, figure things out, and get them done.
• Design and implement AI projects from prototypes to production.
• Balance technical complexity with business impact.
• Collaborate closely with business stakeholders and leadership.
• Explore and utilize our tech stack (and go beyond it when needed).

What You’ll Bring

• Experience with AI frameworks and tooling (Pydantic AI, Langfuse, or alternatives).
• Strong skills in Python and SQL, experience with analytical databases (Snowflake or similar).
• Familiarity with workflow orchestration (Airflow or similar).
• Ability to turn prototypes into production-ready solution using AI and ML.
• Pragmatic approach: balance between business value and technical complexity.
• Proactivity and autonomy – you don’t wait for perfect tasks.
• Strong communication skills for working with leadership and stakeholders.

Your team and stakeholders

For now you will be in tandem with Jana. She is an experienced go to person for our company leadership. In future you will also have other colleagues since we plan to scale this domain.

Why should you apply?

• You will attend our beautiful Karlín Offices with free snacks, grill parties and many educational events.
• This role has direct access to leadership, your work won’t get lost in layers of management.
• High autonomy from the start – no waiting for perfect tasks, you’ll own problems and solve them.
• We give you room to experiment, fail fast, and learn quickly.
• You will work in a small, tight team – your impact will be visible from the beginning.