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Jaroměř, Česko
Remote only
Not Available
We're building our data capabilities and looking for a hands-on Lead Analytics Engineer to take ownership of our data function. As our first dedicated analytics hire, you'll own the pipelines, models, metric definitions, reporting, and data quality that our operations teams and leaders rely on to run the business.
In this role, you'll work closely with leadership and cross-functional teams to turn operational questions into trusted data products, establish consistent definitions for the metrics that matter, and automate reporting that is currently assembled manually.
This is a hands-on builder role, not a people-management role. You'll write SQL, build and operate pipelines, and create models yourself. At the same time, you'll have the autonomy to determine priorities, establish analytics standards, and challenge or clarify requests when the underlying business question or data definition is unclear.
This role is ideal for an experienced analytics professional who is energized by ownership, ambiguity, and the opportunity to build a trusted analytics capability from the ground up.
Build and Operate Integrations: Stand up and own reliable ingestion from systems such as NetSuite, Jira/service platforms, and custom applications. Monitor pipelines, troubleshoot failures, and ensure data arrives accurately and reliably.
Drive Business Intelligence: Own our BI layer (currently utilizing HEX), with the opportunity to evaluate and migrate to tools like Tableau or Looker as we scale.
Partner with Leadership: Work hand-in-hand with the COO to translate operational goals into data models, dashboards, and actionable insights.
Own Data Quality & Governance: Establish trusted metric definitions, documentation, testing, and data-quality standards. Maintain the metric dictionary and clearly communicate when data is incomplete or should not be relied upon.
Automate Operational Reporting: Take ownership of recurring operational reporting, ad hoc analysis, SLA reporting, and client review data. Build repeatable, automated solutions that replace manual reporting processes.
Experiment & Innovate: Stay creative. We want someone who suggests new tools, tests experimental models, and constantly looks for better ways to solve problems.
Cross-Functional Partnership: Act as the primary data consultant for operations, finance, and engineering leaders. Translate their real-world operational challenges into data models and actionable, automated dashboards.
Roles & Responsibilities
The "Hybrid" Professional: You sit comfortably at the intersection of Data Engineering (building pipelines, data modeling) and Data Analytics (BI, dashboards, telling stories with data).
Meticulous & Detail-Oriented: You care deeply about clean code, accurate numbers, and reliable pipelines. You build appropriate tests and controls so leaders can trust the numbers they use to make decisions.
An Entrepreneurial Builder: You are excited by a blank canvas. You want to get your hands dirty, build from scratch, and take extreme ownership of your work.
Curious & Adaptive: You love to learn, experiment with new technologies, and pivot quickly when a better solution presents itself.
A High-Impact Communicator: You don't just love data; you love talking to the people who use it. You can sit down with a warehouse manager or a software engineer, understand their pain points, and build a data solution that makes their job easier.
Experience: 5+ years of experience across analytics engineering, data engineering, or analytics, including meaningful experience building data models and pipelines that others depend on. Experience as the first or only data practitioner is strongly preferred.
Cloud Data Warehousing: Strong, hands-on experience with Snowflake (architecture, performance tuning, and optimization).
SQL & Pipeline Mastery: Advanced SQL skills are a must. Experience with integration/ETL tools (Celigo, Fivetran, dbt, or custom API scripting) is highly valued.
BI & Visualization: Experience building impactful dashboards. Familiarity with HEX is a major plus; experience with Tableau, PowerBI, or Looker is required.
Ecosystem Familiarity: Experience working with data originating from ERPs (NetSuite), project management tools (Jira), and custom web applications.
Autonomy: Demonstrated ability to operate with limited structure, identify the highest-value analytics work, set priorities, and move from problem definition through delivery without waiting for a backlog of assigned requests.
