Data Modeller

Antal Poland; Kraków; Hybrid; PLN 120,000 - 170,000; Full time

Job summary

Antal Poland is seeking a Data Modelling specialist in Kraków to design, implement, and document data architectures across SQL, NoSQL, and cloud platforms. The role focuses on building conceptual, logical, and physical data models to support BI, analytics, and data science initiatives.

You will collaborate with Data CIOs and product teams, govern data standards, and drive data modelling best practices while working in a hybrid setup (2 days in the office, 3 days remote).

Qualifications

• 3+ years of hands-on relational, dimensional, and/or analytic experience with RDBMS, dimensional, NoSQL data platforms and ETL/data ingestion protocols.
• MongoDB experience would be an advantage.
• Experience with data warehouse, data lake, and enterprise big data platforms is preferred.

Responsibilities

• Implement data strategies and designs across all data platforms (SQL/NoSQL) and data tools (reporting, analytics, ML).
• Collaborate with business and solution teams to develop data models and data flows.
• Define and govern data modelling standards, tools, and best practices for enterprise data models.
• Identify data sources, interfaces, and security considerations for automated data loads and analytics models.
• Hands-on data modelling, design, configuration, and performance tuning; create sandbox POCs.
• Work independently and with teams to meet project requirements and reduce delivery risks.

Skills

Relational data modeling

Dimensional modeling

NoSQL data platforms

ETL and data ingestion

MongoDB

Tools

Erwin

Visual Paradigm

MongoDB

Job description

Location

Kraków, hybrid work model – 2 days per week in the office, 3 days remote

Project for our Client from the financial sector

The team

The team's organisation consists of individuals working both on global, regional, and local projects in support of all Global Businesses and Global Functions. The individual(s) in the role of Data Modelling will be responsible for modelling data within specific Businesses, Functions and/or Geographies and will work with the Data CIOs and Data Officers and their respective teams as needed.

The Role

The data modeler designs, implements, and documents data architectures and data models for solutions, which include the use of application, relational, dimensional, and NoSQL databases. These solutions support enterprise information management, business intelligence, operations, machine learning, data science, and other business interests.

The successful candidate will:

• Be responsible for the development of the conceptual, logical, and physical data models, oversight of the implementation of RDBMS, operational data stores (ODS), application databases, data marts, and data lakes on target platforms (SQL/NoSQL/cloud/on-prem)
• Oversee and govern the expansion of existing data architecture and the optimization of data query performance via best practices. The candidate must be able to work independently and collaboratively

Responsibilities

• Implement business and IT data requirements through new data strategies and designs across all data platforms (application, relational, dimensional, and NoSQL) and data tools (reporting, visualization, analytics, operations, and machine learning)
• Work with business and application/solution teams to implement data strategies, build data flows, and develop conceptual/logical/physical data models
• Define and govern data modelling and design standards, tools, best practices, and related development for enterprise data models
• Identify the architecture, infrastructure, and interfaces to data sources, tools supporting automated data loads, security concerns, analytic models, and data visualisations
• Hands-on modelling, design, configuration, installation, performance tuning, and sandbox POC
• Work proactively and independently to address project requirements and articulate issues/challenges to reduce project delivery risks

Requirements:

• 3+ years of hands‑on relational, dimensional, and/or analytic experience (using RDBMS, dimensional, NoSQL data platform technologies, and ETL and data ingestion protocols). Experience on MongoDB would be an advantage
• Good knowledge of metadata management, data modelling, and related tools (Erwin or Visual Paradigm or others) required
• Experience with data warehouse, data lake, and enterprise big data platforms in multi‑data‑centre contexts is desired
• Experience in team management, communication, and presentation
• Strong communication skill, good oral English