- Data Engineering
in Hungary
Discover our world of professional growth with EPAM Hungary's quality engineering team!
Career Opportunities
Disciplines Insights
Let's explore the diverse domains you can operate in and smoothly navigate between.
Data Software Engineering
Data Software Engineering
As a data software engineer, your day involves managing and organizing data from various sources, akin to sorting and arranging puzzle pieces. You transform raw data into a usable format, employing technical skills such as coding and database management. Your work supports our data scientists and analysts, who use the data you prepare to make crucial business decisions. Though often behind the scenes, your role is pivotal in shaping our company's success through data-driven insights.
Tech stack:
- Apache Spark
- Python
- Scala
- Apache Beam
- SQL
- RDBMS
- Azure/AWS/GCP
- Unix/Linux
- dbt
- Snowflake
- Google BigQuery
- Amazon Redshift
- Databricks
- Hive
- Apache Airflow
Data Analytics & Visualization Engineering
Data Analytics & Visualization Engineering
Data Analytics and Visualization Engineers blend skills from two related fields. On one side, like Data Integration Engineers, they design target models, manage source data ingestion, create data transformations and pipelines, and build data warehouses. On the other hand, similar to Business Intelligence Engineers, they process data from marts, implement analytic measures, design functions, and use visualization techniques to present data clearly.
By covering tasks from both the back-end and front-end of the data analytics technology stack, a Data Analytics and Visualization Engineer unifies the skills of two interrelated disciplines in one person.
Tech stack:
- RDBMS products: MS SQL Server, Oracle, PostgreSQL, MySQL, Azure SQL Server, AWS RDS, GCP Cloud SQL
- Data Warehousing solutions: Snowflake, BigQuery, Azure Synapse, RedShift
- Data Integration tools: Azure Data Factory, AWS Glue, GCP Dataflow, Talend, Informatica, Pentaho, Apache KNIME, SSIS
- Data Visualization tools: PowerBI, Tableau, QlikView, Looker, Tibco
- Programming languages: SQL, Python, SparkSQL, PySpark, R, DAX
- Cloud platforms: Azure, AWS, GCP
- Cloud components: Storage, Compute, Networking, Identity and Security
- CI/CD and Versioning tools: Jenkins, Unit Testing, Git/GitHub/Gitlab
Business Intelligence Analysis
Business Intelligence Analysis
A Business Intelligence Analyst (BIA) is a customer-facing data and technology specialist who combines business analysis knowledge and interpersonal and data skills to turn business needs into data solutions.
This includes:
- Speaking the customer language and solving their challenges through data
- Leading requirement gathering and management activities
- Delivery of data discovery and data modeling
- Managing data assessment requirements
- Using modern data visualization tools and prototypes to validate requirements
- Preparing signed-off requirements for mass-scaled delivery (user story slicing, requirement management, estimation, prioritization) for a development team
- Conducting demo sessions
- Facilitating the UAT phase
In terms of tech skills, BIAs have a good understanding of the modern cloud-based technology stack (in the fields of data and analytics) and are aware of data visualization and data-driven storytelling best practices, big data terms and stack and machine learning fundamentals.
Typical project roles for a BIA include serving as a business analyst on data projects, data analyst, proxy product owner or product owner.
Tech stack:
- PowerBI
- Tableau
- SQL
- DOMO
- Spotfire
- Excel
- Jira
- Confluence
- Colibra
- Looker
- QlikSense/View
- PowerPoint
- Visio
- Draw.io
- Lucidchart
Data Science
Data Science
Data science is an interdisciplinary field that utilizes scientific methods, algorithms, and techniques to extract valuable insights and knowledge from various data sources, both structured and unstructured. It combines elements of computer science, mathematics, statistics, and domain expertise to enable evidence-based decision-making and drive innovation across industries.
Our expertise covers every aspect of the data science journey — from engineering and preprocessing to model development, validation and deployment. Each of us is committed to crafting personalized, cutting-edge solutions that suit our clients' specific needs and to assist them making better decisions and uncover new business opportunities.
Tech stack:
- Python
- Jupyter
- Scikit-learn
- XGBoost
- Pytorch
- LangChain
Machine Learning Engineering
Machine Learning Engineering
As a Machine Learning Engineer, you are a skilled architect. Your specialty? Designing and deploying machine learning models that unlock solutions to real-world problems. This role combines a deep grasp of Machine Learning with solid Software Engineering skills to create reliable and efficient ML pipelines.
In harmony with Data Scientists, you are part of transforming early-stage models into ready-for-action tools, perfectly integrated into existing structures. You enable data-driven decision-making and automation, fostering business growth and innovation across various industries.
Tech stack:
- ML Pipelines (AWS SageMaker pipelines, GCP Vertex AI pipelines, Azure ML Pipelines, Kubeflow Pipelines)
- MLFlow/Kuberflow
- AirFlow
- Spark
Data DevOps
Data DevOps
As a Data DevOps Engineer, you're like a skilled conductor orchestrating a balanced data ecosystem. Your tasks range from designing and upkeeping data infrastructure to automating data deployment processes. You work in tandem with data teams to enable seamless deployment of data-related applications while keeping an eye on system performance. You're at the forefront, troubleshooting issues during deployment, while ensuring data security and compliance are met. Paired with your expertise in Big Data technologies, you also work with data engineers to safeguard efficient data handling processes.
Tech stack:
- Data pipelines: ML Pipelines (AWS SageMaker pipelines, GCP Vertex AI pipelines, Azure ML Pipelines, Kubeflow Pipelines)
- Clouds: AWS/Azure/GCP
- Languages: Python, bash
- Automation: Terraform, Ansible, AWS SDK
- CI/CD Versioning tools: GitHub/Gitlab/Bitbucket, AWS Code Build/Pipeline, Jenkins
- Kubernetes
- Databricks
- AirFlow, Snowflake
Data Solution Architecture
Data Solution Architecture
As a Data Solution Architect, imagine yourself as a mediator between the business world and technological realms. By deciphering business requirements, your role is to create a blueprint of cost-effective, maintainable, scalable parallel and distributed systems for data processing in the cloud. More importantly, you ensure its implementation upholds the highest quality standards, paving the way for a smooth, technology-driven business operation.
Tech stack:
- AWS & Azure managed services in data;
- Databricks
- Snowflake
- MS Fabric
Data Analytics Consulting
Data Analytics Consulting
As part of our Data Analytics Consulting practice, you'll serve as the navigator of data-driven transformations. Your mission is to discover business improvement opportunities, analyze business challenges, and suggest the best solutions. From shaping the product strategy to judging its business value, you'll handle it all, ensuring the actionable nature of these plans. Serving as an advocate for data analytics, you'll connect customer vision and requirements to precise deliverables - charting the path to improved business performance.
Skills:
- Data Strategy
- Data Governance
- Master Data Management
- Data Architecture
- Cloud Platforms
- GenAI, MLOps
- Business Value Understanding
Data Delivery Management
Data Delivery Management
As a Data Delivery Manager, you're a specialist in ensuring successful end-to-end delivery of top-tier Data & Analytics solutions using the latest technologies, often cloud-based. Here at EPAM, you're the keystone establishing robust partnerships between business and technology, guiding our clients towards success. This multifaceted role harnesses your data-focused perspective and passion for people, blending hands-on delivery skills with theoretical understanding from both Data & Analytics and Project Management fields.
Skills:
- Data Strategy
- Data Governance
- Master Data Management
- Data Architecture
- Cloud Platforms
- GenAI, MLOps
Use Cases
AWS-based Genomic Analysis System
Image recognition and integrated Databricks platform
Evolve with EPAM
Join EPAM and grow your professional career. With our structured career path, you can build on your existing educational background. Become an EPAMer, where you'll find opportunities for development and success.
EPAM Campus Programs
EPAM Campus Programs
Jumpstart your Career with EPAM
Seeking to embark or advance your career in IT? At EPAM, we provide many educational opportunities, ranging from self-paced introductory courses to in-depth internships, all tailored to boost your career journey in various IT fields.
Explore our extensive catalog to see where your talents and skills fit. You can access these opportunities from any location and on a flexible schedule — all remotely delivered.
Start your career with us through our unique program, EPAM Campus. Dive deep into diverse technology areas, completely free of charge and with no obligations.
Discover the right opportunity for you with EPAM, where your career in IT can take off.
Welcome to our Learning and Development universe
Welcome to our Learning and Development universe
We are delighted to share our internally developed resources to support your personal growth, even if you are not yet part of the EPAM family. Visit our Learning Portal and customize your educational pathway using our multifaceted tools.
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