About SunnyData: At SunnyData, a leading Databricks technology partner, our mission is to empower customers with scalable architectures, robust data engineering pipelines, seamless data consumption layers, and advanced ML and AI applications. As a Senior Solutions Architect, you will be instrumental in driving customer success, both in terms of technical execution and pre-sales support.

• Customer Engagement: Serve as a trusted advisor to customers, guiding them through their data engineering and data architecture needs with a focus on Databricks solutions. In this role you will split your time evenly between billable and pre-sales activity.

• Technical Leadership: Design, build, and deploy comprehensive data solutions that capture, transform, and leverage data to support AI, ML, and business intelligence initiatives.

• Pre-Sales Support: Collaborate with sales teams to present technical solutions to prospective clients, demonstrating the value of SunnyData's offerings.

• Project Oversight: Manage multiple customer accounts, ensuring timely delivery of solutions and tracking progress to report outcomes.

• Solution Design: Architect data solutions, incorporating best practices in data governance, security, and quality.

• Data Analysis: Evaluate data sources for their value, recommending data inclusion strategies to enhance analytical processes.

• Cross-Functional Collaboration: Work closely with internal teams to deliver solutions and educate end users on data products and analytic environments.

• Problem Resolution: Perform system analysis, assess and resolve data and system defects, and apply appropriate corrections.

• Quality Assurance: Test data movement, transformation code, and data components to ensure accuracy and reliability.

Required Experience:

• Experience: 5-7+ years as a hands-on Solutions Architect and/or Sr. Data Engineer designing and more recent experience implementing data solutions with a focus on DataBricks.

• Technical Proficiency: Expertise in Data Engineering technologies (e.g., Spark, Hadoop, Kafka), Databricks platform, and data science/machine learning technologies (e.g., pandas, scikit-learn).

• Architecture and leadership skills: In-depth understanding of the end to end data analytics workflow (e.g., data modeling, ETL processes, and data integration) using modern data engineering techniques; Ability to lead complex architecture requirements(discovery), solution design sessions and build out implementation architecture blueprints that can be implemented by data-engineering and analytics teams.

• Certifications (at least 2 of the following): Associate Developer for Apache Spark; Data Engineer Associate; Professional Data Engineer; Machine Learning Associate; Professional ML Engineer

• Programming Skills: Proficiency in Java, Python, and/or Scala.

• Cloud Platforms: AWS, Azure, and/or GCP.

• SQL Expertise: Ability to write, debug, and optimize SQL queries.

• Client-Facing Skills: Strong written and verbal communication skills with experience in client-facing roles.

• Presentation Skills: Ability to create and deliver detailed presentations to clients and stakeholders.

• Documentation: Experience in creating detailed solution documentation including POCs, roadmaps, sequence diagrams, class hierarchies, and logical system views.

• Team Leadership: Experience leading teams and mentoring other engineers.

• End-to-End Solutions: Ability to develop end-to-end technical solutions into production, ensuring performance, security, scalability, and robust data integration.
  
  Preferred Experience:

• Distributed Storage: Familiarity with cloud and distributed data storage systems such as S3, ADLS, HDFS, GCS, Kudu, ElasticSearch/Solr, Cassandra, or other NoSQL storage systems.

• Data Integration: Experience with data integration technologies like Spark, Kafka, Streamsets, Matillion, Fivetran, NiFi, AWS Data Migration Services, Azure DataFactory, and Informatica Intelligent Cloud Services (IICS).

• Software Development Lifecycle: Comprehensive experience with the complete software development lifecycle including design, documentation, implementation, testing, and deployment.

• Automated Pipelines: Expertise in automated data transformation and curation using tools like dbt, Spark, Spark streaming, and automated pipelines.

• Workflow Management: Experience with workflow management and orchestration tools like Airflow, AWS Managed Airflow, Luigi, and NiFi.

• Education: 4-year Bachelor's degree in Computer Science or a related field.

Benefits

• Health Insurance : Employees and their eligible family members including spouses, domestic partners, and children are eligible for coverage from the first day of employment.

• Paid Time Off : Start your career at SunnyData with a minimum of 20 days Paid Time Off annually, plus nine paid company Holidays.

• An opportunity to grow your technical and people skills, lead teams on complex customer projects that are highly innovative and cutting edge. Great opportunity to grow in your career with the right level of focus, innovation and customer centricity with a high growth consulting company dedicated to Databricks.

Compensation Overview

• The annual base salary range provided for this position is a nationwide market range and represents a broad range of salaries for this role across the country. The actual salary for this position will be determined by a number of factors, including the scope, complexity and location of the role; the skills, education, training, credentials and experience of the candidate; and other conditions of employment. As part of our comprehensive compensation and benefits program, employees are also eligible for performance-based cash incentive awards.

Our Commitment to Diversity and Inclusion

• At SunnyData, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at SunnyData are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.