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 Solutions Architect, you will be instrumental in driving customer success, both in terms of technical execution and pre-sales support. Serve as a trusted advisor to customers, guiding them through their data engineering and data architecture needs with a focus on Databricks solutions.

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

Project Oversight: 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. Lead internal teams, provide direction and mentorship to project teams to deliver solutions and educate end users on data products and analytic environments. 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. 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. Expertise in Data Engineering technologies (e.g., Spark, Hadoop, Kafka), Databricks platform, and data science/machine learning technologies (e.g., pandas, scikit-learn).

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. Proficiency in Java, Python, and/or Scala.

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

SQL Expertise: Ability to write, debug, and optimize SQL queries. Ability to develop end-to-end technical solutions into production, ensuring performance, security, scalability, and robust data integration. 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. Expertise in automated data transformation and curation using tools like dbt, Spark, Spark streaming, and automated pipelines.

Experience with workflow management and orchestration tools like Airflow, AWS Managed Airflow, Luigi, and NiFi.

Associate

Developer for Apache Spark

- Data Engineer Associate
- Professional Data Engineer
- Machine Learning Associate
- Bachelor's Degree in Computer Science or Engineering related field. All qualified applicants will receive consideration for employment without regard to race, religion, gender identity, disability, veteran status, or any other protected characteristic. Work with cutting-edge technologies and industry leaders in data engineering and AI. Make a real difference in how businesses leverage data for strategic decision-making. Opportunities for professional development and career advancement. If you are passionate about data engineering and enjoy engaging with clients to solve their most challenging problems, we would love to hear from you.

📌 Senior Solutions Architect - work remote (Lerdo)
🏢 Sunnydata
📍 Lerdo