Jobs at Hiflylabs

Own the architecture and production delivery of LLM, RAG, agentic, and classical ML systems. Design scalable AI solutions on Databricks using Spark and MLflow, optimize latency, cost, reliability, and performance, and implement evaluation, monitoring, CI/CD, rollback, and versioning. Translate client needs into end-to-end architectures, lead technical decisions and pre-sales discussions, and mentor team members on GenAI and ML best practices.

Manage and migrate ETL pipelines across source systems, validate pipeline builds and data quality, resolve pipeline issues and discrepancies, and support data migrations. Provide operational support in Snowflake, collaborate with business stakeholders and subject matter experts, document work, and maintain data engineering best practices. The role requires SQL, Python, Pandas or PySpark, advanced Excel, analytical problem-solving, and familiarity with modern data engineering tools.

Design and develop scalable Databricks Lakehouse solutions across major cloud platforms. Build Delta Lake pipelines, data models, governance layers, and secure access using Unity Catalog. Write SQL and Python, automate deployments with DABs and CI/CD, and orchestrate workflows. Manage technical delivery components, estimation, testing, documentation, and stakeholder collaboration while leveraging cloud-native storage and security services.

Design and implement modern data architectures and lakehouse solutions using cloud platforms and tools such as Databricks and Snowflake. Provide technical leadership, stakeholder collaboration, pre-sales expertise, effort estimates, team mentoring, and code reviews. The role involves long-term project-based consulting with flexible full-time or part-time engagement and occasional onsite client work.

Lead end-to-end data science and AI/ML projects with a product-oriented mindset. Engage clients to translate business goals into technical solutions, lead pre-sales discussions, and integrate machine learning and generative AI capabilities into products. Apply expertise in Python, SQL, traditional machine learning, deep learning, NLP, LLMs, RAG, and cloud platforms. Provide technical leadership, mentorship, and guidance on selecting appropriate AI and ML approaches.

Coordinates internal reporting, business operations, AI adoption, process optimization, and data-driven solutions. Supports Power BI and Google Sheets reporting, data warehouse alignment, AI tools and automated workflows, data governance, IAM, and privacy compliance initiatives. Collaborates with back-office teams and the CTO on operational projects, internal communications, chatbots, and AI agents while helping expand global operations.

Senior Data Engineer responsible for aligning data solutions with business needs, architecting data models and cloud lakehouse platforms, leading technical delivery and testing, supporting pre-sales estimation and proposals, and mentoring project teams. The role requires consultancy experience, technical leadership, strong communication in English and Hungarian, and hands-on expertise with Databricks, Snowflake, Azure, or AWS data platforms.

Lead customer-facing architecture and implementation of large-scale Databricks and Apache Spark solutions. Design production data pipelines, optimize performance, guide data engineering and model deployment, and align technical roadmaps with business objectives. Deliver technical leadership, training, tutorials, hackathons, and presentations while supporting strategic stakeholders. The role requires extensive big data, cloud, programming, CI/CD, testing, and consulting experience.

Supports business operations through data organization, analysis, process improvement, automation, AI experimentation, troubleshooting, and data quality checks. The intern will use tools such as spreadsheets, AI assistants, APIs, and workflow integrations to reduce manual work and improve operational efficiency. The role also involves communicating with colleagues, investigating issues, following established processes, and identifying practical improvements.

Lead international presales for data platform consulting, partnering with Sales, architects, and delivery teams to shape solutions, define scope, estimate costs, assess risks, and win projects. Build client relationships, lead proposals and negotiations, ensure effective handoffs to delivery, and occasionally sponsor or lead projects. Contribute to business-unit leadership, cross-functional collaboration, and team development while serving primarily English-speaking clients.

Provide post-sales technical leadership for strategic customers implementing Databricks and big data solutions. Design production architectures, optimize end-to-end pipelines, guide data engineering and model deployment, identify data-value initiatives, and deliver training, tutorials, hackathons, and presentations. The role requires advanced Apache Spark and Databricks expertise, cloud experience, strong programming skills, customer-facing consulting ability, and business-fluent English and German.

Lead enterprise-wide data platform implementations on Databricks from ingestion through Medallion architecture and modern BI or agentic AI consumption layers. Manage delivery, Scrum ceremonies, budgets, compute costs, risks, scope, technical backlogs, and stakeholder alignment. Partner with Product Owners and Data Architects while guiding data engineering and data science teams and translating C-level business requirements into technical execution.

This position invites you to express your interest in future opportunities and connect with the organization for potential roles, aligning your motivations with their projects.

The Business Analyst will map business needs, create specifications for IT projects, liaise between stakeholders and development teams, and define metrics for product performance.

The DevOps Engineer will design, develop, and deploy development tools and infrastructure, automate processes, ensure security and compliance, and assist with incident management and microservices integration.

The role focuses on creating and implementing Data & AI strategies, advising executives, and managing projects to drive AI adoption and business growth.

Advise clients on data-driven decision-making, lead discovery and solutioning, define KPI and semantic models, and design and build executive and tactical Power BI dashboards. Drive reporting governance, translate analysis into clear visual narratives, coordinate cross-functional teams, and use AI tools to improve analytical and consulting workflows.

Build end-to-end web applications across frontend and backend. Lead technical decisions, implement scalable solutions, integrate frontends with REST APIs, use Python backends and Databricks, write unit/integration/end-to-end tests, deploy to cloud using Docker and CI/CD, and collaborate with designers, customers, and engineers to ensure timely, high-quality feature delivery.

Lead architecture and hands-on development of cloud-native AI web applications. Design end-to-end solutions integrating LLMs, vector search/RAG, real-time data, and scalable backend services. Implement model serving, RAG pipelines, AI agents, and ensure quality via testing and CI/CD while leading cross-functional engineering teams and translating business requirements into production-ready systems.

Senior customer-facing role designing and implementing large-scale Databricks/Spark data platforms. Provide technical leadership post-sales, architect production workloads, optimize pipeline performance, deliver training and presentations, and drive initiatives that turn data into business value while mentoring and supporting clients.