Principal Solutions Architect (Financial Services)
- Compensation
- Not disclosed
- Location
- United States
- Work setup
- Remote
- Seniority
- Principal
- Employment
- Not specified
- Experience
- 10+ years
- Category
- Architecture
- Posted
Skills
Must have
- Experience: 10+ years as a hands on Solutions Architect and/or Senior Data Engineer, with recent experience implementing data solutions on Databricks.
- Technical Proficiency: Expertise in data engineering technologies (Spark, Hadoop, Kafka), the Databricks platform, and data science/ML tooling (pandas, scikitlearn).
- Architecture & Solution Design: Deep understanding of the end to end data analytics workflow (data modeling, ETL, data integration) using modern engineering techniques. Able to run complex architectur
- Programming Skills: Proficiency in Java, Python, and/or Scala.
- Cloud Platforms: AWS, Azure, and/or GCP.
- SQL Expertise: Able to write, debug, and optimize SQL queries.
- Client Facing Skills: Strong written and verbal communication, with experience in client facing roles.
- Presentation Skills: Able to build and deliver detailed presentations to clients and stakeholders.
- Documentation: Experience producing detailed solution documentation, including POCs, roadmaps, sequence diagrams, class hierarchies, and logical system views.
- End to End Solutions: Able to take technical solutions into production, ensuring performance, security, scalability, and robust data integration.
- Team Leadership: Experience managing, mentoring, and growing a team of engineers.
Nice to have
- 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 C
- 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.
- Location: residing in Pacific Time or on the West Coast are strongly preferred.
Full description
SunnyData is a leading Databricks technology partner, helping customers build scalable architectures, robust data engineering pipelines, and advanced ML and AI applications. As a Principal Solutions Architect, you'll drive customer success on two fronts: hands on technical execution and presales support, splitting your time evenly between the two.
The Impact You Will Have
- Customer Engagement: Serve as a trusted advisor to customers, guiding their data engineering and architecture strategy with a focus on Databricks solutions.
- Technical Delivery: Design, build, and deploy comprehensive data solutions that capture, transform, and leverage data for AI, ML, and business intelligence initiatives, while driving innovation through thought leadership on data trends.
- Presales Support: Partner 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 and clear reporting on progress and outcomes.
- Solution Design: Architect data solutions that incorporate best practices in governance, security, and data quality.
- Data Analysis: Evaluate data sources for their value and recommend inclusion strategies that strengthen analytics.
- Cross Functional Collaboration & Mentorship: Guide internal teams, provide direction and mentorship to project teams, and educate end users on data products and analytic environments.
- Problem Resolution: Perform system analysis, diagnose data and system defects, and apply the right fix.
- Quality Assurance: Test data movement, transformation code, and data components for accuracy and reliability.
Required Experience
- Experience: 10+ years as a hands on Solutions Architect and/or Senior Data Engineer, with recent experience implementing data solutions on Databricks.
- Technical Proficiency: Expertise in data engineering technologies (Spark, Hadoop, Kafka), the Databricks platform, and data science/ML tooling (pandas, scikitlearn).
- Architecture & Solution Design: Deep understanding of the end to end data analytics workflow (data modeling, ETL, data integration) using modern engineering techniques. Able to run complex architecture discovery, solution design sessions, and build implementation blueprints that engineering and analytics teams can execute.
- Programming Skills: Proficiency in Java, Python, and/or Scala.