Dreamix

• Design and own scalable, production-grade data pipelines across the medallion architecture (ingestion, transformation, serving). • Define and enforce canonical data models aligned to business domains. • Architect pipelines for scalability, reliability, and cost efficiency, with strong focus on performance tuning (latency, partitioning, compute, SLAs). • Build and optimize data workflows using Databricks (Spark, Delta Lake, Delta Live Tables, Autoloader, Unity Catalog). • Establish robust data quality, validation, and testing frameworks across all pipeline layers. • Ensure reliability through proper handling of retries, idempotency, and failure scenarios. • Partner with data scientists, analysts, and business stakeholders to translate requirements into high-quality data products. • Develop and maintain data integrations and APIs to enable seamless data access and interoperability. • Implement data governance, security, and compliance best practices across the platform. • Mentor and support engineers by setting best practices, providing technical guidance, and contributing to a strong engineering culture. • Troubleshoot, optimize, and continuously improve data infrastructure and workflows based on evolving needs and technologies.

• Innovate and oversee the AI capabilities powering reactive, proactive, and predictive customer support across all products and solutions. • Analyze customer issues and risk patterns to embed predictive and preventative AI capabilities directly into the support lifecycle. • Lead the ideation, prototyping, and scaling of AI-driven solutions from Proof of Concept (PoC) to full production. • Collaborate closely with engineering, operations, product, and customer-facing teams to implement, optimize, and align solutions with business objectives. • Continuously evaluate new AI tools and technologies to improve efficiency, accuracy, scalability, and data compliance. • Act as a mentor within a network of AI and technical experts, sharing best practices, lessons learned, and driving value realization and adoption.

• Lead end-to-end delivery of technology projects and programs — from initial scoping and planning through execution to release • Go beyond status reporting: proactively identify blockers, dig into problem areas, and drive resolution together with the team • Define and manage project scope, timelines, budgets, and resource plans in alignment with business objectives • Coordinate work across cross-functional teams (development, QA, DevOps, business stakeholders) in multinational and hybrid setups • Own risk and issue management — surface problems early, escalate when needed, and ensure timely resolution • Build strong relationships with stakeholders at all levels, from engineering teams to executive leadership • Communicate project progress, key decisions, and release plans clearly and consistently • Drive change management and support the adoption of new processes, tools, or platforms • Work closely with technology leadership to align delivery with the broader technical and business roadmap • Create and maintain clear project documentation — plans, reports, and decision logs • Foster a culture of collaboration, accountability, and continuous improvement within project teams

• Design and develop agentic AI systems that can retrieve relevant information and interact with tools and services to support and automate operational workflows in cloud environments • Design and implement agentic AI systems capable of reasoning, planning, and executing tasks across complex operational environments • Develop AI agents that can interact with tools and services, including APIs, monitoring systems, knowledge bases, and operational platforms • Build mechanisms for context and knowledge retrieval, enabling agents to access documentation, historical data, and structured information required for decision-making • Implement autonomous or semi-autonomous workflows where AI agents assist humans by analysing situations, proposing actions, and executing tasks where appropriate • Develop scalable backend services and interfaces that allow agents to interact with enterprise systems and cloud platforms • Deploy and operate agent-based solutions in cloud-native environments, ensuring reliability, observability, and maintainability

• Design visuals for various company needs: presentations, social media, case studies, articles, newsletters, quarterly reports, and infographics • Create engaging video content for Social Media and our website • Ensure designs are visually appealing and aligned with brand guidelines • Collaborate with different departments to design print materials (Talents and Culture, Business Development, Partnership Management, etc.) • Design new landing pages to enhance user experience • Keep up-to-date with the latest design trends, tools, and technologies

• Design, build, and maintain data pipelines across ingestion, transformation, and delivery layers • Implement transformations that apply business rules and produce clean, governed datasets • Ensure pipelines are performant, observable, and maintainable • Develop data quality checks, tests, and validations to meet data contracts and business requirements • Investigate and resolve data quality issues in development and production • Adhere to agreed engineering standards, naming conventions, and code review practices • Ensure all work is documented, version-controlled, and maintainable by the team • Collaborate with engineering and data stakeholders on pipeline design and data requirements

• Lead teams of data engineers and analytics professionals, providing technical direction and mentorship across the project lifecycle • Architect and implement cloud-native data platforms on AWS, designing schemas and ingestion pipelines that handle structured data from diverse sources including Excel feeds, legacy databases, and third-party systems • Design, develop, and maintain ETL/ELT pipelines using AWS Glue and Step Functions, ensuring reliable data transformation, validation, and quality enforcement at every stage • Own the infrastructure-as-code practice using Terraform — provisioning, versioning, and managing all cloud resources with full reproducibility and environment consistency • Deliver end-to-end reporting solutions through Power BI, translating complex data models into intuitive dashboards that provide stakeholders with actionable, near-real-time insights • Translate complex technical concepts and architectural decisions to non-technical stakeholders clearly and persuasively, facilitating informed decision-making at all levels • Establish and enforce best practices around data quality, pipeline monitoring, documentation, and incident response • Participate in pre-sales and discovery efforts, leveraging technical expertise to support scoping, estimation, and business development initiatives

Dreamix was founded 19 years ago by passionate IT students who wanted to create the dreamiest workplace where everyone is heard, works under transparent management, and lives up to their full potential. Now, many years later, we deliver software solutions for renowned companies from Germany, the UK, Switzerland, and Silicon Valley. We believe that the employer-employee relationship must be in the form of partnership, not transaction. We are committed to investing as much as possible in our employees and we expect the same from you. About the Role: We are looking for a skilled and motivated Lead Data Engineer to drive the design, implementation, and evolution of cloud-native data platforms on AWS. In this role, you will own the end-to-end architecture of data ingestion, transformation, and delivery pipelines — from heterogeneous source systems through to executive-facing BI dashboards. You will combine deep technical expertise with strong stakeholder engagement to ensure data solutions are robust, scalable, and aligned with business needs. Responsibilities: - Lead teams of data engineers and analytics professionals, providing technical direction and mentorship across the project lifecycle - Architect and implement cloud-native data platforms on AWS, designing schemas and ingestion pipelines that handle structured data from diverse sources including Excel feeds, legacy databases, and third-party systems - Design, develop, and maintain ETL/ELT pipelines using AWS Glue and Step Functions, ensuring reliable data transformation, validation, and quality enforcement at every stage - Own the infrastructure-as-code practice using Terraform — provisioning, versioning, and managing all cloud resources with full reproducibility and environment consistency - Deliver end-to-end reporting solutions through Power BI, translating complex data models into intuitive dashboards that provide stakeholders with actionable, near-real-time insights - Translate complex technical concepts and architectural decisions to non-technical stakeholders clearly and persuasively, facilitating informed decision-making at all levels - Establish and enforce best practices around data quality, pipeline monitoring, documentation, and incident response - Participate in pre-sales and discovery efforts, leveraging technical expertise to support scoping, estimation, and business development initiatives Requirements: - Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related field - 7+ years of experience in data engineering, cloud infrastructure, or platform development, with a demonstrated track record of delivering production-grade data solutions - Strong hands-on experience with AWS data services — particularly Glue, Step Functions, S3, RDS/Redshift, IAM, and CloudWatch - Proficiency in SQL and Python for data transformation, pipeline orchestration, and scripting - Solid experience with Terraform or equivalent IaC tooling for managing cloud infrastructure - Proven ability to design and optimize ETL/ELT pipelines for data ingestion from heterogeneous sources - Experience building dashboards and data models in Power BI (or equivalent BI tools such as Tableau or Looker) - Strong understanding of data modeling, schema design, and data warehousing concepts - Exceptional communication, presentation, and stakeholder management skills — comfortable leading technical discussions with engineering teams and presenting insights to C-level audiences alike - Strong leadership capabilities with experience mentoring engineers and driving best practices across teams Nice to Have: - Experience with additional AWS services such as Lambda, Athena, Lake Formation, or EventBridge - Familiarity with CI/CD pipelines for data infrastructure (e.g., GitHub Actions, CodePipeline) - Exposure to data governance, cataloging, or lineage tooling - Experience working in consulting or multi-client delivery environments What you’ll get: - A collaborative, knowledge-sharing culture built on transparency and mutual respect - Flexible working hours that allow you to balance your work and personal life - Unlimited home office to help you stay productive and focused - Opportunities for professional development, including certifications and training - Additional benefits for academic teaching and speaking engagements - Knowledge-sharing sessions where you can learn from our Dreamix team - Team and company-wide events that bring us together - Amazing week long summer office and winter office initiatives - Additional health insurance and dental allowance to ensure your well-being - Multisport card to encourage a healthy and active lifestyle - Office massages to help you relax and unwind If you find the mentioned above interesting, send us your CV! Only shortlisted candidates will be contacted. The confidentiality of all applications is assured! By applying for this job, you voluntarily agree and submit your personal information. Any personal data that you provide will be processed in strict confidentiality by Dreamix ltd. only for the purposes of selection and recruitment and will not be transferred to other data controllers unless required by law. It will be stored, processed, retrieved, and deleted in accordance with the GDPR.

• Prepare the process of test planning, coverage and estimation within a small to medium team • Collaborate with the development team to understand software requirements and design comprehensive test scenarios and cases • Maintains and extends the available automation testing framework • Develop and maintain automated test scripts for front-end & back-end testing • Execute automated and manual tests, analyze results, and report defects, providing clear and detailed documentation • Continuously identify areas for test improvement and implement innovative approaches to enhance efficiency and effectiveness • Participate in code reviews and contribute to the overall quality and stability of the software • Stay up-to-date with industry best practices and emerging technologies related to automation testing • Research new tools and technologies • Supports and extends the existing CI/CD pipelines in their test provisioning and execution part

• Design, develop, and maintain scalable data pipelines for processing and analyzing large volumes of data • Develop and optimize data workflows using Databricks, leveraging Spark for large-scale data processing • Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and ensure data integrity and quality • Utilize your expertise in Python for scripting and coding tasks related to data processing and analysis • Understand and implement business rules in Python for data transformation • Implement ETL processes to integrate data from various sources into data warehouse or data lake solutions • Optimize big data storage and processing • Troubleshoot and resolve data-related issues, ensuring the reliability and performance of our data infrastructure • Follow emerging trends and technologies in the data engineering space and make recommendations for continuous improvement • Optimize and tune data workflows for maximum efficiency and scalability. • Implement data security best practices to protect sensitive information and ensure compliance with data protection regulations. • Develop and maintain API integrations to facilitate seamless data exchange between systems and applications