About the Job/What will you do?
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. This is a remote role (with possible rare exceptions to be agreed upon in due time) and requires the applicant to have a significant time zone overlap with the 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.).
Requirements
- 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.
Why us?