SunnyData Principal Solutions Architect at SunnyData responsible for customer success through technical execution and presales support. Design and deploy data solutions leveraging Databricks and modern data engineering technologies.
Responsibilities
Serve as trusted advisor guiding data engineering and architecture strategy
Design, build, and deploy data solutions for AI, ML, and BI initiatives
Partner with sales teams to present technical solutions to clients
Manage multiple customer accounts ensuring timely delivery and reporting
Architect data solutions incorporating governance, security, and quality
Evaluate data sources and recommend inclusion strategies
Guide internal teams and mentor project teams
Perform system analysis and diagnose data/system defects
Test data movement, transformation code, and data components
Qualification
Proficiency in JavaExperience with cloud platforms AWSStrong SQL skillsDistributed StorageData IntegrationSoftware Development LifecycleAutomated PipelinesWorkflow ManagementDomain KnowledgeRegulatory Compliance
Required
10+ years as a hands on Solutions Architect and/or Senior Data Engineer
Recent experience implementing data solutions on Databricks
Expertise in data engineering technologies (Spark, Hadoop, Kafka)
Proficiency in Java, Python, and/or Scala
Experience with cloud platforms AWS, Azure, and/or GCP
Strong SQL skills
Experience in client facing roles and presentations
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 Data Factory, and Informatica Intelligent Cloud Services (IICS).
Software Development Lifecycle: Comprehensive experience with the complete SDLC, 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.
Domain Knowledge: Background working in the Financial Services industry, preferably in a banking environment.
Regulatory Compliance: Understanding of industry compliance requirements and standards, specifically in banking IT landscapes.
Certifications (at least 2 of the following): Associate Developer for Apache Spark, Data Engineer Associate, Professional Data Engineer, Machine Learning Associate, Professional ML Engineer.
