We are seeking an experienced and driven Senior Data Engineer to join our expanding Data Engineering team. In this role, you will be a key member of one of our established Platform Teams, designing, developing, and scaling data pipelines in Databricks with PySpark on Microsoft Azure for the AI Factory team. This is an exciting opportunity to work at the intersection of big data and cloud engineering, delivering reliable, scalable, and high-performance data platforms that drive innovation across our organization.
responsibilities
Design cloud-native analytical solutions using Big Data and NoSQL technologies
Build and optimize scalable data pipelines in Databricks with PySpark on Azure
Develop and maintain data lakes and data warehouses to ensure reliability and performance
Design and implement ETL/ELT workflows to collect, clean, and structure data
Implement data quality, lineage, and monitoring frameworks
Collaborate with ML and analytics teams to deliver clean, production-ready datasets
Conduct code reviews to uphold technical standards and best practices
Mentor junior engineers and foster a high-performance, collaborative culture
Integrate CI/CD methodologies into data engineering workflows using tools such as Jenkins or GitLab CI/CD
Support requirements gathering and deliver solutions in alignment with architects, technical leads, and cross-functional teams
Engage with stakeholders to understand business processes, model input data, and ensure deliverables meet requirements
requirements
4+ years of experience in Data Engineering or a related field
Proficiency in Python and PySpark
Hands-on experience with Databricks and Microsoft Azure cloud services
Familiarity with software version control tools (e.g., GitHub, Git)
Experience with CI/CD frameworks such as Jenkins, Concourse, or GitLab CI/CD
Proven ability to build scalable, robust, and highly available data solutions
Strong problem-solving, analytical, and stakeholder engagement skills
nice to have
Experience with additional programming languages such as Java, SQL, or Scala
Knowledge of SAP BTP or similar enterprise data platforms
We are seeking a visionary and experienced Lead Data Engineer to join our Data Engineering team. In this role, you will lead a Platform Team, driving the design, development, and scaling of data pipelines in Databricks with PySpark on Microsoft Azure for our AI Factory team. This is a unique opportunity to shape the future of our data platforms, influence technical strategy, and mentor a talented team, all while working at the forefront of big data and cloud engineering.
responsibilities
Lead the design and architecture of cloud-native analytical solutions using Big Data and NoSQL technologies
Oversee the development and optimization of scalable data pipelines in Databricks with PySpark on Azure
Own the strategy for building and maintaining data lakes and warehouses, ensuring reliability, performance, and scalability
Define and implement ETL/ELT workflows and best practices for data collection, cleaning, and structuring
Establish and enforce data quality, lineage, and monitoring frameworks across the team
Collaborate closely with ML, analytics, and business teams to deliver production-ready datasets and solutions
Conduct and lead code reviews, setting technical standards and fostering best practices
Mentor and coach data engineers, cultivating a high-performance and collaborative team culture
Champion CI/CD methodologies in data engineering workflows using tools like Jenkins or GitLab CI/CD
Drive requirements gathering and solution alignment with architects, technical leads, and cross-functional teams
Engage with stakeholders at all levels to understand business processes, model input data, and ensure deliverable alignment with strategic goals
requirements
6+ years of experience in Data Engineering or a related field, with at least 2 years in a technical leadership role
Deep proficiency in Python and PySpark
Extensive hands-on experience with Databricks and Microsoft Azure cloud services
Strong background in software version control tools (e.g., GitHub, Git)
Proven track record with CI/CD frameworks such as Jenkins, Concourse, or GitLab CI/CD
Demonstrated expertise in architecting and building scalable, robust, and highly available data solutions
Excellent problem-solving, analytical, and stakeholder management skills
Experience in mentoring and leading engineering teams
nice to have
Experience with additional programming languages such as Java, SQL, or Scala
Knowledge of SAP BTP or similar enterprise data platforms
Familiarity with agile development methodologies
Experience in strategic planning and technical roadmap development
We are looking for a motivated Data Engineer to join our growing Data Engineering team. You will work as part of one of our Platform Teams, developing and maintaining data pipelines in Databricks with PySpark on Microsoft Azure for the AI Factory team. This role offers the opportunity to work with modern cloud and big data technologies, contributing to reliable and scalable data platforms that support innovation across the organization.
responsibilities
Develop and maintain data pipelines in Databricks with PySpark on Azure
Support the design and implementation of cloud-based analytical solutions using Big Data and NoSQL technologies
Assist in building and maintaining data lakes and warehouses to ensure reliability and performance
Participate in the development of ETL/ELT workflows to collect, clean, and structure data
Help implement data quality, lineage, and monitoring frameworks
Collaborate with ML and analytics teams to deliver clean, production-ready datasets
Participate in code reviews and follow technical standards and best practices
Work with CI/CD methodologies in data engineering workflows using tools like Jenkins or GitLab CI/CD
Collaborate with architects, technical leads, and cross-functional teams to deliver solutions aligned with requirements
Engage with stakeholders to understand processes and ensure deliverable alignment
requirements
2+ years of experience in Data Engineering or a related field
Proficiency in Python and PySpark
Experience with Databricks and Microsoft Azure cloud services
Familiarity with software version control tools (e.g., GitHub, Git)
Exposure to CI/CD frameworks such as Jenkins, Concourse, or GitLab CI/CD
Ability to build reliable and scalable data solutions
Strong problem-solving and analytical skills, with effective communication and teamwork abilities
nice to have
Experience with additional programming languages such as Java, SQL, or Scala
Knowledge of SAP BTP or similar enterprise data platforms
We are seeking an experienced and highly motivated Data Engineer to join our expanding Data Engineering practice. This role will enhance one of our established Platform Teams, where you will design, construct, and scale data pipelines using Databricks with PySpark on Microsoft Azure, enabling our AI Factory teams to create and deploy advanced machine learning solutions. This position offers a unique opportunity to work at the crossroads of big data, cloud frameworks, and MLOps, delivering durable, scalable, and efficient data platforms that promote innovation throughout the organization.
responsibilities
Design analytical solutions using Cloud Native, Big Data, and NoSQL technologies
Build scalable data pipelines with Databricks and PySpark on Azure
Collaborate with MLOps and ML Engineering teams to deliver robust data platforms for AI model development and deployment
Work alongside architects, technical leads, and cross-functional teams to align solutions with business objectives
Assist the SAP Platform Team in utilizing SAP BTP and hyperscaler services for enterprise-grade data platforms
Conduct and participate in code reviews to ensure adherence to technical standards and best practices
Mentor junior engineers to cultivate an innovative and high-performance engineering culture
Implement CI/CD practices into data workflows using tools like Jenkins, GitLab CI/CD, and Concourse
Facilitate communication with stakeholders to understand business processes, model input data, and deliver aligned solutions
requirements
Minimum of 2 years' experience in Software Engineering with a solid background in Data Engineering, Machine Learning Operations, or Machine Learning
Expertise in Python and PySpark
Familiarity with Databricks and Microsoft Azure cloud services
Strong knowledge of software version control tools like GitHub or Git
Background in CI/CD tools such as Jenkins, GitLab CI/CD, or Concourse
Proven capability to deliver scalable, robust, and highly available data solutions
Competency in problem-solving, analytical thinking, and managing stakeholder relationships
nice to have
Skills in another programming language such as Java, SQL, or Scala
Understanding of SAP BTP or comparable enterprise data platforms
We are seeking an experienced and driven Senior Data Engineer to join our expanding Data Engineering team. This position involves working as part of one of our established Platform Teams, where you will design, develop, and scale data pipelines in Databricks with PySpark on Microsoft Azure, empowering our AI Factory teams to create and deploy advanced machine learning solutions. This role offers the chance to contribute at the nexus of big data, cloud engineering, and MLOps, delivering reliable, scalable, and high-performance data platforms that support innovation across the organization.
responsibilities
Design cloud-native analytical solutions using Big Data and NoSQL technologies
Build scalable data pipelines in Databricks with PySpark on Azure
Collaborate with MLOps and ML Engineering teams to deliver data platforms for AI development and deployment
Support requirements gathering and deliver aligned solutions with architects, technical leads, and cross-functional teams
Assist the SAP Platform Team in utilizing SAP BTP and hyperscaler offerings for enterprise-grade data solutions
Conduct code reviews to ensure technical standards and practices are maintained
Provide mentorship to junior engineers to cultivate a high-performance culture
Incorporate CI/CD methodologies into data engineering workflows using tools like Jenkins or GitLab CI/CD
Engage with stakeholders to understand processes, model input data, and ensure deliverable alignment
requirements
4+ years of experience in Software Engineering with a focus on Data Engineering, Machine Learning, or MLOps
Proficiency in Python and PySpark
Background in Databricks and Microsoft Azure cloud services
Knowledge of software version control tools, including GitHub or Git
Capability to work with CI/CD frameworks such as Jenkins, Concourse, or GitLab CI/CD
Expertise in building scalable, robust, and available data solutions
Competency in problem-solving and analytical skills, along with effective stakeholder engagement
nice to have
Skills in an additional programming language like Java, SQL, or Scala
Understanding of SAP BTP or similar enterprise data platforms
We are seeking a highly skilled and detail-oriented Senior Data Engineer to join our growing team in Birkirkara. In this role, you will be a key contributor to build and optimize our data infrastructure, pipelines and analytics systems. You will be responsible for designing, building and maintaining highly scalable and secure ETL/ELT data pipelines to support the needs of analytics, data science and business teams. The ideal candidate has strong technical expertise, problem-solving skills and leadership capabilities to support the development of a scalable and robust data engineering ecosystem. This role offers a hybrid work setup, providing flexibility to work both remotely and in-office, helping you achieve a balanced professional and personal life.
responsibilities
Architect and maintain modern data platforms, warehouses and lakes (e.g., Snowflake, BigQuery, Redshift, Databricks)
Optimize the storage and retrieval of data and ensure performance and cost efficiency
Establish processes and systems for monitoring data quality, completeness and reliability
Automate manual processes and optimize data delivery workflows to reduce latency and improve job reliability
Implement and maintain Kafka-based streaming data pipelines for real-time data processing and integration with various systems
Integration to third party databases and APIs
Continuously refine and improve existing data systems and pipelines for scalability
Implement monitoring and alerting systems for data pipelines
Ensure data infrastructure uptime and availability
requirements
Minimum 5–8+ years of experience in data engineering or related roles, including experience with large-scale data processing
Proficiency in programming languages like Python, SQL
Expertise in building and maintaining ETL/ELT workflows using tools like Apache Airflow
Hands-on experience with Big Data technologies like Spark, Hadoop and Kafka
Working experience with version control systems (Git) and CI/CD pipelines
We are seeking a Senior Data Scientist with proficiency in classical Machine Learning and practical production experience in at least one of the following areas: NLP, Time Series, MLE/MLOps (Machine Learning Engineering/Operationalization), or Recommendation Systems. This role provides an opportunity to lead projects, mentor junior colleagues, and tackle diverse, high-impact challenges. You will work directly with internal teams, client executives, vertical owners, and technical teams. If you are ready to embrace new challenges, we welcome your application to join our dynamic team.
responsibilities
Lead the assessment, design, development, and deployment of end-to-end ML solutions
Collaborate with internal teams and clients to define and resolve business problems using data and AI-driven solutions
Own the model lifecycle, spanning research, experimentation, and production monitoring
Mentor junior team members and promote coding and ML workflow best practices
Maintain up-to-date knowledge of advancements in Machine Learning and AI
requirements
Minimum of 5 years’ production experience in Data Science or Machine Learning
Proficiency in the Python ecosystem and data science libraries such as Pandas, scikit-learn, and NumPy
Strong SQL skills with experience in managing large and complex datasets
Expertise in at least one ML domain, including NLP, CV, Time Series, or Recommenders
Background in working with Databricks, including Notebooks, MLflow, and data processing via Apache Spark
Capability to utilize Deep Learning frameworks, such as PyTorch or TensorFlow
Familiarity with Docker, Kubernetes, and model-serving strategies
Background in leveraging cloud platforms like AWS, GCP, or Azure
We are seeking an accomplished, forward-thinking leader in Data Management & Governance to work collaboratively with our client in delivering exceptional business outcomes. In this role, you’ll engage closely with senior executives, shape impactful strategies, and leverage modern data technologies to drive organizational transformation. If you’re passionate about solving complex challenges and redefining data management excellence, this is the perfect opportunity. Our client is investing heavily in their Data Management & Governance consulting practice, combining efficient data governance with cutting-edge technology to build a dynamic, high-growth environment centered on innovation. With an agile culture, they empower you to tackle complex, high-visibility challenges for leading global organizations. This isn’t just a job – it’s your chance to be at the forefront of data-driven transformation and make a lasting impact. If you’re eager to join a high-performing team where your expertise shapes strategic initiatives, we’d love to hear from you.
responsibilities
Engage with senior executives to define and execute enterprise-wide Data Management & Governance strategies, often becoming a “trusted advisor”
Lead assessments to help clients advance from current to optimal data governance maturity by developing strategies, roadmaps, and implementation plans
Leverage deep business and IT expertise to build Data Management & Governance solutions that drive innovation and create value across client organizations
Deliver end-to-end services, from strategy ideation and use case elaboration to MVP implementation and scaling for enterprise adoption
Guide architectural teams and lead discussions on modern Data Management architecture, ensuring best practices for data lifecycle management
Support business development efforts, including crafting proposals, Statements of Work, and delivering client presentations
Develop consulting offerings and reusable templates to enhance delivery efficiency
requirements
Bachelor's or Master's degree in information technology or a related field
At least 3 years of experience in a consulting role, leading Data Management & Governance initiatives
In-depth knowledge in 2-3 of the following areas: Data Governance Operating Models & Policies, Data Quality, Master Data Management, Metadata Management & Data Cataloguing, Data Lineage, or Data Compliance
Familiarity with data governance frameworks like DAMA or DCAM, and an understanding of their practical implementation
Proven ability to build relationships with directors and C-level stakeholders, understand business needs, and deliver data-driven insights
Experience conducting maturity assessments, gap analyses, and developing strategic roadmaps with implementation guidelines
Skilled in running client workshops to identify priorities, assess current states, and evaluate readiness for enterprise Data Management & Governance initiatives
Knowledge of market trends, technology selection models, and best practices tailored for large-scale application
Hands-on experience with the modern data stack, working in agile environments with advanced technologies
Ability to work independently, manage small projects with multiple workstreams, or oversee parts of larger engagements
Strong verbal and written English skills for leading discussions and producing clear, concise documentation
nice to have
Experience in leading data transformation projects
Technology expertise with one or several commercial or open-source tools, e.g. Collibra, Alation, Informatica, Ataccama, Azure Purview, Atlas, Talend, Soda
Understanding of modern concepts as Data Observability, DataOps and Data Mesh
Technology expertise in modern Big Data & Cloud stack: Spark, Snowflake, Databricks, etc.
Practical expertise in implementation of Data Governance for modern cloud data lakes
We are seeking a dedicated and skilled Presales Solution Consultant to become a key member of our growing Data & AI practice. This position blends technology with business strategy, empowering clients to leverage data for transformative outcomes. You will be instrumental in designing cutting-edge data solutions, advancing sales efforts, and delivering exceptional strategic insights through your consulting and technical expertise. Our ideal candidate possesses strong technical acumen combined with outstanding consulting abilities, excels in dynamic settings, and ensures alignment between client needs and modern data and analytics capabilities. This opportunity allows you to engage with groundbreaking technologies and contribute to impactful results across global industries.
responsibilities
Collaborate with sales, delivery, and expert teams to align client objectives with tailored data-driven solutions, ensuring our offerings address business challenges
Manage all facets of the presales process, including qualification of opportunities, solution design, proposal creation, demonstrations, and client presentations
Facilitate workshops and meetings to understand client goals and technical needs, ensuring our solutions align with their business objectives
Develop comprehensive data solutions featuring cloud-native platforms, data integration, advanced analytics, and AI/ML models for actionable insights
Craft compelling proposals, pricing models, and value propositions to successfully secure opportunities and convert engagements
Monitor updates and advancements in Data & Analytics, Cloud, and AI spaces while providing strategic recommendations to clients and driving innovation within the practice
Enhance operational efficiency by contributing to reusable solution frameworks, accelerators, and methodologies
Foster team development through mentorship and knowledge-sharing initiatives
requirements
Qualifications in Data Science, Computer Science, Business Analytics, or comparable professional expertise
Extensive background (5+ years) in presales, solution architecture, or consulting, emphasizing Data/AI technologies and their application in business contexts
Deep knowledge of data platforms (e.g., Databricks, Snowflake, AWS/Azure/GCP Data Services), ETL processes, data modeling, BI tools, and frameworks (e.g., Power BI, Tableau)
Familiarity with data science methodologies combined with proficiency in identifying solutions that meet client needs
Exceptional communication skills with proficiency in conveying complex technical concepts through clear, engaging storytelling
Showcase of experience in interacting with senior stakeholders and delivering impactful pitches or presentations
Competency in creating proposals, RFP responses, and pricing/engagement models for data-related projects or services
Understanding of strategic consulting principles and capability to design future-state roadmaps and solutions for client innovation
Strong organizational and leadership qualities paired with flexibility to manage intricate tasks within fast-paced settings
Proficiency in English communication (B2 level or higher), ensuring technical concepts are clearly understood by diverse audiences
We are seeking a skilled, motivated, and forward-thinking Senior Java Software Engineer to enhance our dynamic team at EPAM Bulgaria. In this position, you'll collaborate with leading professionals, solve advanced technical problems, and support the development of scalable, high-performance solutions for a prominent technology-focused client. This role also offers opportunities to mentor, design, and create systems from the ground up.
responsibilities
Design software components and microservices from the ground up
Cover all phases of the software development lifecycle (SDLC) from a technical perspective
Collaborate with engineers, architects, and product managers to develop and maintain performance-driven platforms
Use advanced technologies within a modern tech stack
Recommend scalable architectural solutions
Foster a productive development workflow emphasizing code quality and maintainability (e.g., TDD, Clean Code, pair programming)
Participate in design discussions, code reviews, and team ceremonies
Mentor and coach junior team members
Communicate with client stakeholders to provide project updates, address priorities, and resolve technical concerns
requirements
5+ years of software development experience with a proven record of producing end-to-end solutions
Expertise in Java and Microservices architecture
Background in the Spring ecosystem, including Spring Boot, Spring Cloud, Spring Data, and Spring Security
Proficiency in REST APIs, Microservices concepts, and relational database design
Knowledge of Design Patterns and their application
Competency in TDD/ATDD and writing testable code
Familiarity with CI/CD tools, particularly Jenkins
Understanding of Clean Code and Software Craftsmanship principles
Strong analytical thinking, problem-solving, and debugging capabilities
Capability to communicate effectively and negotiate in English
Commitment to contributing to collaborative workflows like code reviews and pair programming
Experience mentoring and guiding team members
nice to have
Knowledge of Google Cloud Platform (GCP) or other cloud-native development environments
Background in Guice, Guava, and Protocol Buffers
Skills in Big Data technologies or non-relational databases
Expertise in creating and maintaining real-time business-critical systems
Familiarity with event-driven architecture and distributed systems