Hiflylabs

• As a Senior Solutions Architect, you will play a pivotal role in shaping the future of big data for top Fortune 500 companies. • This senior customer-facing position requires extensive expertise in Apache Spark and a broad range of experience in big data solution architecture. • Each week, you will assist customers with architecture, design, and implementation, ensuring their technical roadmap aligns strategically with the expansion of the Databricks platform. • As a member of the architect team, you will continuously enhance your technical skills through mentorship, ongoing learning, and internal training programs. • Provide technical leadership post-sales to guide strategic customers in designing and implementing big data projects, from architectural design to data engineering and model deployment. • Identify and drive new initiatives that help customers turn their data into actionable business value, aligning these initiatives with their business goals for continued success. • Architect production-level workloads, including performance testing and optimization of end-to-end pipeline loads. • Deliver tutorials and training sessions to promote community adoption (including hackathons, conference presentations, etc.).

• Develop native Swift/iOS applications • Design user interfaces and functions as planned • Take part in requirements gathering, project and technical planning • Write Unit and UI tests, participate in developer testing • Stay up-to-date with current technology trends in iOS development • Work closely with teammates, helping each other • Develop applications for businesses in all sizes

Role Description As a Senior Solutions Architect, you will play a pivotal role in shaping the future of big data for top Fortune 500 companies. This senior customer-facing position requires extensive expertise in Apache Spark and a broad range of experience in big data solution architecture. - Assist customers with architecture, design, and implementation, ensuring their technical roadmap aligns strategically with the expansion of the Databricks platform. - Continuously enhance your technical skills through mentorship, ongoing learning, and internal training programs. - This is a remote role (with possible rare exceptions) and requires significant time zone overlap with clients. Main Tasks - Provide technical leadership post-sales to guide strategic customers in designing and implementing big data projects, from architectural design to data engineering and model deployment. - Identify and drive new initiatives that help customers turn their data into actionable business value, aligning these initiatives with their business goals for continued success. - Architect production-level workloads, including performance testing and optimization of end-to-end pipeline loads. - Deliver tutorials and training sessions to promote community adoption (including hackathons, conference presentations, etc.). Qualifications - Hands-on and technical expertise with Apache Spark. - Hands-on experience with Databricks over the course of several large-scale projects. - Databricks Certified Data Engineer Professional certification. - Proven experience in designing and implementing big data technologies, including Hadoop, NoSQL, MPP, OLTP, OLAP. - Over 5 years of experience working as a Software Engineer or Data Engineer, including query tuning, performance tuning, troubleshooting, and debugging Spark and/or other big data solutions. - Proficiency in programming with Python, Scala, or Java. - Experience designing and using solutions on cloud infrastructure and services, such as AWS, Azure, or GCP. - Familiarity with Development Tools for CI/CD, Unit and Integration testing, Automation and Orchestration, REST API, BI tools, and SQL Interfaces (e.g., Jenkins). - Excellent communication skills and comfort in presenting to strategic stakeholders and leadership. - Experience in customer-facing roles such as pre-sales, post-sales, technical architecture guidance, or consulting. - Passion for learning new technologies and ensuring customer success. - Desired experience in Data Science/ML Engineering, including model selection, model lifecycle, hyper-parameter tuning, model serving, deep learning, using tools like MLFlow. Benefits - Diverse projects - In each assignment, there is always something new, either on the technical or the business side, that helps you grow. - Empowerment - Trust is a cornerstone of our culture. We'll hold your hand if you need it, but give you space if you’d like to push your limits. - Flexible ways of working - We respect our people to do their work when and how they work best. - Balanced life - We highly value fresh minds, for which we think a healthy work/life balance is essential! - Mentoring from your first day - Continuous support is not just a set of fancy words; your mentor follows you throughout your career path. - Learning & Development opportunities - We look forward to helping you unlock your potential. - Supportive corporate culture - We are proud of the social cohesion that is based on comradery, mutual support, and respect.

• Project-Specific Security Design: Conduct security reviews and design secure architectures for data-driven and AI-powered systems, including cloud environments on AWS, Azure, and GCP • Risk Assessment: Perform threat modeling activities with a strong focus on data security and vulnerabilities related to LLMs and AI models (e.g., OWASP Top 10 for LLM Applications) • Compliance Support: Assist projects in meeting regulatory and compliance requirements, including GDPR, ISO 27001, NIS2, and the EU AI Act • Consulting & Stakeholder Engagement: Participate in client discussions, clarify security requirements, and ensure proper documentation of security-related decisions and controls

• Provide technical leadership post-sales to guide strategic customers in designing and implementing big data projects, from architectural design to data engineering and model deployment. • Identify and drive new initiatives that help customers turn their data into actionable business value, aligning these initiatives with their business goals for continued success. • Architect production-level workloads, including performance testing and optimization of end-to-end pipeline loads. • Deliver tutorials and training sessions to promote community adoption (including hackathons, conference presentations, etc.).

• Strategic Roadmap Ownership: Define the "Why" and the "What" for our Databricks-based projects. • Partner with stakeholders to prioritize high-ROI AI features. • Requirements Gathering and User Stories: translate complex stakeholder needs into actionable user stories and technical requirements. • Business Logic Interpretation: help technical counterparts understand complex business logic and translate it into a technical context. • Cross-Functional Orchestration: Lead regular syncs between the engineering team and key stakeholders at the customer, ensuring that technical delivery stays aligned with business strategy. • Testing and Quality Assurance: Lead QA (Quality Assurance) and UAT (User Acceptance Testing) of features developed by technical team while maintaining a feedback loop to ensure stakeholder-developer alignment. • Identify additional opportunities at the customer and build a strong relationship with the key stakeholders.

• Design and implement scalable AWS cloud architectures with a strong focus on networking and platform stability • Architect and manage AWS networking components (VPCs, routing, egress control, hybrid connectivity) • Build and maintain Databricks platform architecture on AWS, ensuring best practices and scalability • Develop and manage Infrastructure as Code (IaC) using Terraform, with a focus on reusable and modular design • Define and implement cost allocation models across tenants and projects • Design and develop CI/CD pipelines (e.g., Declarative Automation Bundles – DAB) to enable automated deployments • Collaborate with internal stakeholders to define platform standards, governance, and best practices • Drive automation initiatives to reduce manual operations and improve reliability

• Define the "Why" and the "What" for our Databricks-based projects. • Partner with stakeholders to prioritize high-ROI AI features. • Translate complex stakeholder needs into actionable user stories and technical requirements. • Help technical counterparts understand complex business logic and translate it into a technical context. • Lead regular syncs between the engineering team and key stakeholders at the customer, ensuring that technical delivery stays aligned with business strategy. • Lead QA (Quality Assurance) and UAT (User Acceptance Testing) of features developed by technical team while maintaining a feedback loop to ensure stakeholder-developer alignment. • Identify additional opportunities at the customer and build a strong relationship with the key stakeholders.

• Own the architecture and delivery of production-grade LLM systems and classical ML solutions • Design, evaluate, and optimize RAG pipelines (retrieval strategy, chunking, indexing, monitoring) • Build scalable, production-grade LLM services and agentic workflows, alongside traditional ML systems where appropriate • Define architecture trade-offs (LLM vs traditional ML, fine-tuning vs RAG, hosted vs self-managed models), with a strong focus on system-level optimization (latency, cost, scalability, reliability) • Architect and optimize distributed GenAI and ML workloads on Databricks (Spark, MLflow), leveraging deep understanding of the platform ecosystem • Implement evaluation frameworks to measure quality, hallucination, and performance • Productionize systems with proper CI/CD, monitoring, rollback, and versioning • Independently design AI solutions tailored to client problems, translating business needs into scalable architectures • Lead technical decisions in client engagements and actively contribute to pre-sales architecture discussions • Mentor team members and define GenAI and ML best practices.

• Collaborate with cross-functional teams (developers, product managers, stakeholders) to create user-centered designs that meet business goals and user needs • Design intuitive and visually appealing interfaces for web and mobile applications, ensuring a seamless user experience • Conduct user research, competitive analysis, and usability testing to inform design decisions • Create wireframes, prototypes, and high-fidelity mockups to communicate design ideas effectively • Iterate on designs based on feedback from users and stakeholders in an agile environment • Ensure design consistency with brand guidelines while staying current on design trends and best practices • Work closely with developers to ensure designs are accurately implemented and functional • Stay up to date with the latest UI trends, techniques, and technologies