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

THE ROLE

As a Data Engineer - Agentic AI focus you will architect the high-performance data ecosystem that transforms raw information into actionable intelligence and agentic AI solutions. You will bridge the gap between complex engineering and business impact, collaborating with Data Scientists and Product Managers to build the infrastructure that scales our AI capabilities. This isn't just about moving data; it’s about engineering the foundation for the next generation of automated customer support and operational excellence.

WHAT YOU'LL DO

• Architect Scalable Data Infrastructure: Design, deploy, and optimize production-grade ETL pipelines and data models that ensure high-quality, AI-ready datasets for global business intelligence.
• Drive AI Evolution: Lead the technical preparation and prototyping of AI-driven workflows, integrating emerging LLM frameworks to automate complex business processes and enhance decision-making.
• Ensure Data Excellence and Integrity: Own the end-to-end data management lifecycle, implementing robust governance, security, and monitoring to maintain a "single source of truth" for critical stakeholders.
• Collaborate and Solve Across Functions: Partner with cross-functional teams to translate business needs into technical specifications, serving as the bridge that turns raw data into measurable organizational impact.
• Operational Reliability: Manage business-hour on-call rotations to ensure the seamless performance of ingestion systems, maintaining high availability for our global data consumers.

WHAT YOU BRING

• Advanced Engineering Proficiency: Deep technical expertise in SQL, Python, and data modeling, with a proven track record of maintaining complex data pipelines and workflow orchestration tools like Airflow or DBT.
• Modern Data Stack Expertise: Hands-on experience managing relational and NoSQL environments (such as Snowflake, PostgreSQL, or MongoDB) within AWS cloud infrastructures.
• Growth Mindset & AI Curiosity: A strong desire to apply traditional data engineering principles to intelligent automation, including the ability to adapt to new technologies like LLM orchestration and model evaluation.
• Collaborative Communication: The ability to distill complex technical concepts into clear insights for non-technical partners, ensuring alignment across global time zones and diverse teams.
• We are primarily an in-office environment and therefore, you will be expected to work from the Prague, Czech Republic office in compliance with Pure’s policies, unless you are on PTO, or work travel, or other approved leave.

#LIONSITE

THE ROLE

As a Software Systems Architect, you will serve as the technical visionary and bridge between complex global business needs and high-quality technical execution. Based in our Prague R&D, you will define the architectural roadmap for engineering teams across Prague and Santa Clara, transforming requirements from Sales, Marketing, HR, and Customer Service into scalable, AWS-native solutions. Your mission is to elevate our engineering standards by architecting cutting-edge Agentic systems and intelligent orchestration layers. This is a high-impact leadership role where you will drive innovation, mentor a growing organization of 30+ developers, and ensure our internal platforms are resilient, secure, and future-proof.

WHAT YOU'LL DO

• Architectural Governance & Design: Lead the end-to-end design of complex, distributed systems by creating high-fidelity blueprints that align technical strategy with internal business goals for scalability and maintainability.
• Hands-on Technical Leadership: Drive "lead-by-example" execution by building Proof of Concepts (POCs), conducting live technical demonstrations, and authoring the gold-standard design documentation that sets the bar for the entire engineering organization.
• Systemic Quality Assurance: Act as the final authority on technical designs, rigorously reviewing architectural proposals to mitigate risks in performance, reliability, and security before they reach production.
• Agentic Systems Innovation: Drive the adoption of Agentic services and prediction models, architecting the orchestration layers that enable AI agents to solve intricate business problems for global stakeholders.
• Technical Mentorship & Culture: Actively coach a community of 30+ developers to improve the collective mastery of design-led development, advanced unit/functional testing practices, and modern coding standards.
• Strategic Collaboration: Partner closely with the Head of Engineering in Santa Clara to translate high-level global roadmaps into actionable technical strategies, ensuring seamless execution across geographic boundaries.
• Operational Excellence: Standardize the integration of complex data environments, ensuring that our architectural patterns support robust data engineering and AI-driven workflows at scale.

WHAT YOU BRING

• Software Engineering Mastery: 10+ years of professional experience in software development and architecture, including  hands-on coding skills in Python (preferred) or Java.
• Technical Influence: A proven "Architect-Coder" mindset with the ability to influence engineering culture through technical excellence, high-quality documentation, and a "quality-first" approach to testing.
• Cloud Architecture Expertise: Deep, hands-on experience architecting resilient microservices and distributed systems within AWS (specifically utilizing SQS, SNS, and SageMaker).
• Agentic AI Proficiency: A sophisticated understanding of Agentic AI architecture, including multi-agent orchestration, LLM-powered tool calling, and the integration of prediction models into business workflows.
• Complex Problem Solving: A track record of resolving highly complex technical challenges involving large-scale data engineering, enterprise integration, or AI-driven automation.
• Enterprise Tooling Integration: Professional familiarity with modern data and integration platforms such as Snowflake, dbt, Fivetran, SnapLogic, Boomi, or Reltio.
• In-Office Collaboration: We are primarily an in-office environment and therefore, you will be expected to work from the Prague office in compliance with Pure’s policies, unless you are on PTO, or work travel, or other approved leave.

 #LI-ONSITE

THE ROLE

We’re building a new capability inside Platform Engineering, within our Infrastructure Shared Services (ISS) organisation: Data Platform Engineering. Our goal is to create a platform that removes friction, providing a consistent way to build, operate, and evolve data-driven services with clear ownership, guardrails, and a strong developer experience. Everpure’s own platform thinking is anchored in the idea of a unified data plane - a single fabric that connects data across locations and delivers consistent, secure data services across protocols and applications.

In this role, you’ll build and operate a trusted, scalable, and intelligent data platform that empowers teams to make faster data-driven decisions while shaping a culture of ownership and innovation to meet the needs of an ever-changing business and technology landscape.

WHAT YOU'LL DO

• Design, build, and operate the core data platform services that enable teams to ingest, model, query, and publish data seamlessly.
• Architect a multi-engine environment (e.g., Trino/Starburst, Dremio, ClickHouse, Postgres/pgLake) with an Iceberg-based lakehouse, prioritizing interoperability, operability, and security.
• Drive platform evolution through experimentation, measuring performance, reliability, and cost trade-offs to standardize high-impact solutions.
• Establish durable corporate knowledge by developing strong defaults, comprehensive documentation, and intuitive self-service interfaces.
• Manage core lakehouse components, including table layout conventions, catalogue integration, and critical lifecycle maintenance patterns such as compaction and optimization.
• Implement robust ingestion patterns for both batch and streaming data, ensuring clear SLAs and highly observable failure modes.
• Enable multi-engine access by configuring connectors and catalog permissions while maintaining strict guardrails for a consistent user experience.

WHAT YOU BRING

• 6+ years of experience in the design and development of data pipeline automation, specifically extracting data from API-based sources.
• Technical expertise in developing complex automation frameworks, data modeling, and ETL processes using SQL, Python, DBT, Apache Airflow, or similar languages.
• Full-stack proficiency across the data stack, with deep knowledge of Python, SQL, and ETL methodologies.
• Hands-on familiarity with the big data ecosystem, including technologies such as Trino, Kafka, and Iceberg.
• A growth mindset characterized by curiosity and a proactive approach to solving complex architectural problems.
• Strong collaborative communication skills, with a proven ability to align and work effectively across diverse technical stakeholder groups.
• We are primarily an in-office environment and therefore, you will be expected to work from the Prague office in compliance with Pure’s policies, unless you are on PTO, or work travel, or other approved leave.

#LIONSITE

At JetBrains, code is our passion. Ever since we started back in 2000, we have been striving to make the strongest, most effective developer tools on earth. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.

The Data Office is responsible for data associated with products, AI, marketing, finance, sales, and more. Our department ensures that all teams at JetBrains have access to up-to-date, reliable, and transparent data and data services.

As part of our growth strategy, we are looking for an experienced, detail-oriented, and self-motivated BI Analyst to develop, maintain, and enhance BI reports and dashboards for our internal customers across corporate functions, including marketing, IT, PMO, and others.

As part of our team, you will:

• Design, develop, and automate reports and dashboards for several of our data domains, such as marketing, IT, and executive reporting.
• Partner with the Data Quality team to define and implement rules that ensure high data reliability standards.
• Continuously engage with other colleagues at JetBrains, including team clients, data partners, data engineers, and data analysts, to gather and refine business requirements.
• Promote best practices in data visualization.
• Participate in both business-driven and technical projects.

We’ll be happy to have you on our team if you have:

• Extensive SQL experience.
• At least three years of experience with Tableau – experience with Metabase or alternative BI tools is a plus.
• Strong knowledge of and experience with dbt.
• Strong attention to detail and the ability to identify small but important differences.
• Ability to work independently, take ownership of tasks, analyze problems, and deliver results within agreed-upon deadlines.
• Fluent English, both written and spoken.
• Proactive mindset.
• Dedication to knowledge sharing and cross-team collaboration.

We’ll be especially thrilled if you have:

• Basic experience in DWH development.
• Basic experience with AWS. 
• Experience in marketing, including marketing metrics, data structures, and marketing data.

Why join JetBrains? 

• Strong base salary. We offer competitive pay that reflects your skills and experience.
• Flexible work location. Enjoy the freedom to work from home or from the office.
• Remote work. Spend up to 30 days per year working remotely from abroad.
• Extra time off. More days to relax, recharge, and do the things you love.
• Medical insurance allowance. Enjoy peace of mind for you and your family
• Learning and development opportunities. Access to conferences, courses, and language classes.
• Relocation support. We help make your move as smooth and stress-free as possible. 
• Language classes. Pick up the local language or sharpen your English skills.
• Fuel your day. Enjoy a hot meal or receive a lunch allowance on workdays.
• Mental health support. To help you feel your best, we provide easy access to professional mental health services.
• Sports benefit. Enjoy an on-site gym or sports club stipend.
• Internal events. Join company-wide celebrations and team gatherings.

*Some benefits may vary depending on location.

#LI-DNI

#LI-KP1

Joining Collibra’s Support team

Collibra is looking for a high-impact Senior Support Engineer to serve as the final technical authority within our global support organization. In this role, you aren’t just a troubleshooter; you are an investigator, a mentor to our Customer Support Engineers, and the ultimate gatekeeper before a ticket reaches Product & Engineering.

You are motivated by the challenge of scaling a growing company and excited by the "hunt" for deep-seated bugs. You focus on quality, knowing exactly what to test to execute change with confidence. At Collibra, the customer is our “True North” and our Support team spearheads that commitment to excellence!

This is a hybrid role based in our Prague office. Our hybrid model means you’ll work from the office at least two days each week. This setup helps us stay connected, work more closely together, and keep making progress as a team.

Senior Support Engineers at Collibra are responsible for

• Being the Subject Matter Expert (SME), bridging the gap between customer-facing support and product development.
• Reviewing and validating complex tickets, ensuring every investigation is exhaustive and root causes are identified before escalating to Engineering.
• Identifying code defects and edge cases in our platform. You don't just find the "what"; you explain the "why."
• Improving observability by identifying logging and monitoring improvements and unblocking customers using our software.
• Acting as a mentor to the Global Support organization providing structured enablement, training sessions, and validated knowledgebase contributions.
• Participating in the on-call rotations when needed to ensure severe issues get addressed as soon as possible.
• Liaising with Product Managers and Engineering to clarify functional requirements and advocate for long-term fixes.
• Act as the final point of technical escalation, joining live sessions with key customers to resolve complex environmental issues and provide expert-level troubleshooting guidance

You Have

• 4+ years in a technical, customer-facing role (ideally SaaS) with at least 2+ years of hands-on development in Java or Python
• Advanced SQL proficiency and the technical depth to perform complex query optimization, alongside a proven track record of resolving intricate JDBC/ODBC integration hurdles and database-level firewall restrictions.
• A proven ability to conduct comprehensive log analysis within distributed environments, bringing together disparate system data to speed up troubleshooting and identify the exact fixes needed to resolve issues.
• A deep understanding of how SaaS platforms interact with on-premise data sources, including troubleshooting networks, proxies and SSL/TLS certificates
• Working knowledge of Kubernetes (K8s) and Linux environments.
• An understanding of metadata structures and data flows across cloud platforms (Snowflake, BigQuery), ETL tools (dbt, Informatica), and BI systems (Tableau, Power BI) (Nice to have)
• The ability to distill complex technical post-mortems into actionable insights for both customers and internal stakeholders.
• A bachelor’s degree or equivalent related working experience is required

• You must have work authorization to work in Prague, CZ.

You are

• A technical authority who brings deep product expertise to the table, serving as the recognized "go-to" expert in your specialized domains.
• An investigator at heart, excited by the challenge of hunting down bugs and resolving complex, non-obvious issues.
• The ultimate advocate for the customer, keeping their needs at the center of every technical decision.
• A technical mentor with the requisite skill to train and assist others, acting as a vital asset to the growth and success of the entire team.
• A collaborative professional who thrives in a cross-functional environment, synchronizing with diverse resources and always prioritizing the team’s collective success.

Measures of success

• Within your first month, you will master the Collibra landscape and our support protocols, partnering with support engineers to shadow their diagnostic processes.
• Within your third month, you will be an active member of our team, and be comfortable investigating issues independently.
• Within your sixth month, you will interact directly with Product Engineering teams to drive platform improvements. You will be the recognized SME for the most complex parts of the system.

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.

Architect the "Source of Truth" for a Global Marketplace

At Groupon, data isn't just a byproduct—it is the product. We are looking for a Senior Data Analytics Engineer to bridge the gap between raw infrastructure and business insight. You won't just write queries; you will architect the semantic layer of our data warehouse, ensuring that every dashboard, AI model, and executive decision is built on a foundation of trust.

This is a high-impact Individual Contributor role for a builder who loves SQL, obsesses over data modeling, and wants to solve complex problems at a global scale.

The AI Advantage 🤖

We don't just analyze AI; we build with it. You will work in an AI-First environment, leveraging LLMs (ChatGPT, Claude, Copilot) daily to:

• Accelerate SQL generation and refactoring.

• Automate documentation and data lineage.

• Build specific "Feature Stores" that power our Machine Learning models.

What You’ll Build & Own

• The Gold Layer: Design and maintain clean, reusable, and documented data marts in BigQuery that serve as the single source of truth for the company.

• Pipeline Orchestration: Build robust ELT pipelines using Airflow or Keboola. If a pipeline fails at 3 AM, your code is resilient enough to handle it.

• Performance Engineering: Optimize SQL for massive scale. You understand clustering, partitioning, and execution plans to ensure we process petabytes without burning the budget.

• Data Governance: Implement automated testing (dbt-style checks) to catch data drift before it hits the dashboard.

The Tech Stack

• Core: Google Cloud Platform (GCP), BigQuery.

• Orchestration: Airflow, Cloud Composer, Keboola.

• Languages: Advanced SQL (Mandatory), Python.

• Visualization: Tableau, Looker (Knowledge of the semantic layer).

Must-Haves

• 5+ Years Experience: You have a track record in Analytics Engineering, Data Engineering, or BI Development.

• SQL Mastery: You write production-grade code. You know the difference between a query that works and a query that scales.

• Data Modeling: Deep understanding of dimensional modeling (Kimball/Star Schema) and modern data stack patterns.

• Builder Mindset: You treat data assets like software products—versioned, tested, and documented.

Ready to build the data engine that powers the future of local commerce? Apply Now.

#LI-KH1 #LI-Hybrid

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]

• Partner with Sales stakeholders to define analytical requirements, metrics, and KPIs, and identify opportunities for improvement.
• Develop and maintain dashboards, reports, and visualizations that provide timely and actionable insights.
• Analyze revenue streams and contribute to forecasting using statistical, heuristic, or machine learning approaches.
• Perform exploratory and ad hoc analyses to support decision-making across Sales and related teams.
• Collaborate with data engineers to design and implement data marts, reporting layers, and ETL pipelines; contribute to our dbt-based analytics infrastructure.
• Support Sales Development and Lead Generation teams by analyzing experiments and campaign performance.
• Monitor data quality across reporting assets and work with data owners to resolve issues.
• Document metrics, dashboards, and data sources, and help stakeholders effectively use analytics tools.
• Promote self-service analytics by enabling teams to access and interpret data independently.

• 5+ years of experience in a BI, data analysis, or similar analytical role.
• Strong SQL skills and experience with Python, R, or another relevant programming language.
• Experience with BI and visualization tools such as Tableau, Power BI, Qlik, DataLens, or similar.
• Understanding of data warehousing concepts, relational databases, and data processing workflows.
• Experience working with structured datasets and building reliable reporting solutions.
• Strong analytical thinking, attention to detail, and curiosity about data.
• Ability to communicate clearly with both technical and non-technical stakeholders.
• Professional working proficiency in English.

• Experience working with Sales, Marketing, or other go-to-market domains, especially in B2B environments.
• Hands-on experience building ETL pipelines and preparing datasets for analytics.
• Experience working with dbt or similar data transformation tools.
• Familiarity with data governance and data quality practices.

#LI-DNI

Your key skills and capabilities: 

• Strong SQL and Python skills  

• Data modelling experience (dimensional, relational, or similar)  

• Experience building and maintaining backend systems  

• Familiarity with Microsoft Azure  

• Understanding of APIs, containers, and backend development best practices 

• Implementing cloud-native data platforms 

• Engineering scalable and reliable pipelines 

• Good knowledge of distributed computing with Spark 

• Understanding of cloud architecture principles and best practices 

• Hands-on experience in designing, deploying, and managing cloud resources 

• Agile ways of working 

• Experience in cloud automation and orchestration using tools such as CloudFormation or Terraform 

• Monitoring and performance tuning of cloud-based applications and services  

Nice to haves:  

• Experience with Snowflake, dbt, CubeJS 

• Experience with Databricks, PySpark, ML workflows  

• Experience with containerized deployments (Docker, Kubernetes, Azure Container Apps).  

• Frontend development experience (React, Next.js, TypeScript)  

• Infrastructure-as-code (Terraform, CloudFormation) 

• Model Deployment & Serving – Deploy and manage ML models using MLflow, Azure ML, SageMaker, or similar, ensuring scalability and performance  

• Monitoring & Retraining – Set up model drift detection, performance monitoring, and automated retraining   

• ML Pipelines & CI/CD – Automate end-to-end ML workflows 

Key tasks:  

• Develop, maintain, and optimise backend services for our SaaS platform  

• Work with SQL and Python daily to build robust data pipelines and transformations  

• Model, structure, and query data to support product features and reporting  

• Integrate and maintain data ingestion flows (e.g., Fivetran, custom connectors)  

• Implement backend APIs (FastAPI) to power our web application  

• Work with our cloud environment (Azure - experience with AWS or GCP also valuable)  

• Collaborate with teammates to plan, build, and deploy features in an Agile way 

• Contribute to CI/CD workflows, monitoring, and infrastructure-as-code 

We expect you to have some knowledge about how to architect, design, develop, deploy, and operate a data platform.