What skills does a data engineer need?

A data engineer needs 23 essential skills including digital data processing, data warehouse, computer science, data analytics, data storage. Core competencies include Developing People, Transdisciplinary Thinking, Communication.

Will AI replace data engineer jobs?

The AI disruption score for data engineer is 81/100 (very high risk). Some tasks may be automated but the role will evolve rather than disappear entirely.

Infocomm TechnologyInformation and communications technology professionalsISCO 2511

data engineer

Data engineers develop the architecture needed to process, manage, and store large amounts of data which will be used by data scientists for analysis. They design the infrastructure and maintain data pipelines and warehouses to leverage data for strategic advantage.

About data engineer

As a data engineer in Poland, you design and develop the sophisticated technological infrastructure that enables organisations to harness the power of big data. Your primary responsibility is to build robust data architecture, establish efficient data pipelines, and maintain scalable data warehouses that data scientists and analysts rely upon for insights and analysis. You work with massive volumes of structured and unstructured data, implementing solutions that ensure data flows smoothly from source systems through processing layers to storage and consumption endpoints.

Your day-to-day work involves architecting data systems, writing code to create and manage databases, designing cloud-based data solutions, and optimising data storage and retrieval performance. You will collaborate closely with data scientists who consume your data products, IT operations teams, and business stakeholders to understand requirements and deliver solutions. Your skills in cloud technologies, database management systems, programming, and system design are critical as organisations increasingly compete on their ability to leverage data for strategic advantage. You must balance technical excellence with practical considerations of cost, scalability, and maintainability.

The Polish job market for data engineers has experienced explosive growth, particularly in Warsaw, Kraków, and Wrocław's thriving technology sectors. Global technology companies, finance institutions, and rapidly digitising domestic enterprises all compete for experienced data engineering talent. Compensation is highly competitive, and career prospects are excellent, with opportunities to progress into data architecture leadership, principal engineer roles, or specialisation in emerging technologies like AI infrastructure and real-time data systems.

Key Work Functions

Core areas of responsibility for a data engineer.

Data Architecture Design

Design scalable and robust data architecture to support current and future organisational needs
Plan data models and database schemas optimised for performance and maintainability
Evaluate and select appropriate database management systems and cloud technologies
Design data warehouse and data lake infrastructure for analytics and reporting

Data Pipeline Development

Develop and maintain efficient data pipelines that extract, transform and load data reliably
Establish data processes and workflows that handle both structured and unstructured data
Implement error handling, data quality checks and monitoring in production data systems
Optimise pipeline performance and manage resource utilisation efficiently

Database Management and Optimisation

Design, build and maintain databases optimised for specific use cases and performance requirements
Use data storage and indexing strategies to maximise query performance
Implement data security measures, access controls and backup strategies
Monitor database health and perform regular maintenance and troubleshooting

Cloud Infrastructure and Data Systems

Design database solutions in cloud environments (AWS, Azure, GCP) with appropriate scaling
Leverage cloud technologies and managed services to reduce operational overhead
Implement automated deployment and infrastructure-as-code practices

Data Integration and Processing

Integrate data from multiple sources and systems into unified data platforms
Apply data processing techniques to clean, validate and prepare data for analysis
Manage quantitative data and handle edge cases in real-world data
Perform dimensionality reduction and feature engineering to optimise downstream analytics

Collaboration and Stakeholder Management

Collaborate with data scientists and analysts to understand requirements and deliver data products
Manage ICT data architecture and ensure alignment with business objectives
Communicate technical concepts to non-technical stakeholders effectively

Do You Have the Skills for This Role?

Core competency requirements inferred from the occupation's skill profile. Take the free assessment to see how you match.

Must-Have Skills (Advanced)

Developing PeopleAdvanced

Transdisciplinary ThinkingAdvanced

Supporting Skills

CommunicationIntermediate

Creative ThinkingIntermediate

European Skills Framework

Skills and knowledge areas required for this occupation based on European classification.

Essential (23)

digital data processingdigital data processingIdentify, locate, retrieve, store, organise and analyse digital information, judging its relevance and purpose.data warehousedata warehouseThe data storage system that analyses and reports on data such as a data mart.computer sciencecomputer scienceThe scientific and practical study that deals with the foundations of information and computation, namely algorithms, data structures, programming, and data architecture. It deals with the practicabil...data analyticsdata analyticsThe science of analysing and making decisions based on raw data collected from various sources. Includes knowledge of techniques using algorithms that derive insights or trends from that data to suppo...data storagedata storageThe physical and technical concepts of how digital data storage is organised in specific schemes both locally, such as hard-drives and random-access memories (RAM) and remotely, via network, internet ...database management systemsdatabase management systemsThe tools for creating, updating and managing databases, such as Oracle, MySQL and Microsoft SQL Server.cloud technologiescloud technologiesThe technologies which enable access to hardware, software, data and services through remote servers and software networks irrespective of their location and architecture.unstructured dataunstructured dataThe information that is not arranged in a pre-defined manner or does not have a pre-defined data model and is difficult to understand and find patterns in without using techniques such as data mining.data modelsdata modelsThe techniques and existing systems used for structuring data elements and showing relationships between them, as well as methods for interpreting the data structures and relationships.manage research datamanage research dataProduce and analyse scientific data originating from qualitative and quantitative research methods. Store and maintain the data in research databases. Support the re-use of scientific data and be fami...use data processing techniquesuse data processing techniquesGather, process and analyse relevant data and information, properly store and update data and represent figures and data using charts and statistical diagrams.establish data processesestablish data processesUse ICT tools to apply mathematical, algorithmic or other data manipulation processes in order to create information.perform dimensionality reductionperform dimensionality reductionReduce the number of variables or features for a dataset in machine learning algorithms through methods such as principal component analysis, matrix factorization, autoencoder methods, and others.use databasesuse databasesUse software tools for managing and organising data in a structured environment which consists of attributes, tables and relationships in order to query and modify the stored data.manage ICT data architecturemanage ICT data architectureOversee regulations and use ICT techniques to define the information systems architecture and to control data gathering, storing, consolidation, arrangement and usage in an organisation.manage quantitative datamanage quantitative dataGather, process and present quantitative data. Use the appropriate programs and methods for validating, organising and interpreting data.store digital data and systemsstore digital data and systemsUse software tools to archive data by copying and backing them up, in order to ensure their integrity and to prevent data loss.design database in the clouddesign database in the cloudApply design principles for an adaptive, elastic, automated, loosely coupled databases making use of cloud infrastructure. Aim to remove any single point of failure through distributed database design...create data setscreate data setsGenerate a collection of new or existing related data sets that are made up out of separate elements but can be manipulated as one unit.manage datamanage dataAdminister all types of data resources through their lifecycle by performing data profiling, parsing, standardisation, identity resolution, cleansing, enhancement and auditing. Ensure the data is fit ...process dataprocess dataEnter information into a data storage and data retrieval system via processes such as scanning, manual keying or electronic data transfer in order to process large amounts of data.develop data processing applicationsdevelop data processing applicationsCreate a customised software for processing data by selecting and using the appropriate computer programming language in order for an ICT system to produce demanded output based on expected input.implement data warehousing techniquesimplement data warehousing techniquesApply models and tools such as online analytical processing (OLAP) and Online transaction processing (OLTP), to integrate structured or unstructured data from sources, in order to create a central dep...

Optional (5)

statisticsstatisticsThe study of statistical theory, methods and practices such as collection, organisation, analysis, interpretation and presentation of data. It deals with all aspects of data including the planning of ...Teradata DatabaseTeradata DatabaseThe computer program Teradata Database is a tool for creating, updating and managing databases, developed by the software company Teradata Corporation.SAS Data ManagementSAS Data ManagementThe computer program SAS Data Management is a tool for integration of information from multiple applications, created and maintained by organisations, into one consistent and transparent data structur...create data modelscreate data modelsUse specific techniques and methodologies to analyse the data requirements of an organisation's business processes in order to create models for these data, such as conceptual, logical and physical mo...analyse pipeline database informationanalyse pipeline database informationRetrieve and analyse different types of information extracted from the databases of pipelines companies. Analyse information such as risks, project management KPIs (key performance indicators), goods ...