At least 7 years of hands-on Solutions Architect experience with Data Security or related areas.
Expertise in at least two of the following: Cloud Security, Cloud Networking, Encryption, Governance, Privacy, Trust, Safety, Authentication, Identity Management, Access Control, Key Management, Inter-Service Authentication, Secure Application Frameworks, or Detection & Response.
Experience designing data platforms on cloud infrastructure and services such as AWS, Azure, or GCP, using cloud security and networking best practices.
Expertise in data engineering technologies such as Spark, Hadoop, and Kafka; the Databricks platform; cloud platforms; security; automation; networking; or identity management.
In-depth understanding of end-to-end data analytics workflows, including data modeling, ETL processes, and data integration, using modern data engineering techniques.
Ability to lead complex architecture discovery and solution design sessions and create implementation architecture blueprints for data-engineering and analytics teams.
Experience with SDLC tooling such as GitHub and GitLab, continuous inspection tools such as SonarQube, and artifact management tools such as Artifactory.
Experience with infrastructure-as-code tools such as Terraform.
Proficiency in Python, Java, or Scala.
Ability to write, debug, and optimize SQL queries.
Experience in client-facing roles and ability to create and deliver detailed presentations to clients and stakeholders.
Experience creating solution documentation, including proofs of concept, roadmaps, sequence diagrams, class hierarchies, and logical system views.
Experience leading teams and mentoring other engineers.
Ability to develop end-to-end technical solutions for production that meet performance, security, scalability, and data integration needs.
A bachelor's degree in Computer Science or an Engineering-related field.
Responsibilities
Serve as a trusted advisor to customers on data engineering and data architecture needs, focusing on Databricks solutions, and split time evenly between billable and pre-sales activity.
Design, build, and deploy comprehensive data solutions that capture, transform, and leverage data for AI, ML, and business intelligence initiatives.
Collaborate with sales teams to present technical solutions to prospective clients and demonstrate the value of the company's offerings.
Architect data solutions that incorporate best practices in data governance, security, and quality.
Evaluate data sources and recommend data inclusion strategies to enhance analytical processes.
Lead internal teams, provide direction and mentorship to project teams, and educate end users on data products and analytic environments.
Perform system analysis, assess and resolve data and system defects, and apply appropriate corrections.
Test data movement, transformation code, and data components to ensure accuracy and reliability.
Desired Qualifications
Familiarity with cloud and distributed data storage systems such as S3, ADLS, HDFS, GCS, Kudu, Elasticsearch/Solr, Cassandra, or other NoSQL storage systems.
Experience with data integration technologies such as Spark, Kafka, StreamSets, Matillion, Fivetran, NiFi, AWS Data Migration Services, Azure Data Factory, and Informatica Intelligent Cloud Services (IICS).
Experience with the complete software development lifecycle, including design, documentation, implementation, testing, and deployment.
Expertise in automated data transformation and curation using tools such as dbt, Spark, Spark Streaming, and automated pipelines.
Experience with workflow management and orchestration tools such as Airflow, AWS Managed Airflow, Luigi, and NiFi.
At least two of the following certifications: Associate Developer for Apache Spark, Data Engineer Associate, Professional Data Engineer, Machine Learning Associate, or Professional ML Engineer.
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 specialized in Platform, Cloud Infrastructure and Security, you will design and implement scalable data infrastructure while meeting security and compliance requirements.
The Impact You Will Have
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 and Leadership : Lead internal teams, provide direction and mentorship to project 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
7+ years as a hands-on Solutions Architect with experience in Data Security or related areas. Expertise in two or more of the following: Cloud Security, Cloud Networking, Encryption, Governance, Privacy, Trust, Safety, Authentication, Identity Management, Access Control, Key Management, Inter-Service Authentication, Secure Application Frameworks, Detection & Response
Infrastructure and Security: designing data platforms on cloud infrastructure and services (AWS, Azure, or GCP), using best practices in cloud security and networking.
Technical Proficiency: Expertise in Data Engineering technologies (e.g., Spark, Hadoop, Kafka), Databricks platform, cloud platforms, security, automation, networking, or identity management
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.
DevOps/DevSecOps: SDLC tooling such as Github, Gitlab, Continuous Inspection such as SonarQube and Artifact Management such as Artifactory
IaC tools like Terraform
Programming Skills: Proficiency in Python, Java, 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.
Certifications (at least 2 of the following): Associate Developer for Apache Spark; Data Engineer Associate; Professional Data Engineer; Machine Learning Associate; Professional ML Engineer
Education:
Bachelor’s Degree in Computer Science or Engineering related field.
Our Commitment to Diversity and Inclusion:
SunnyData is dedicated to building a workforce that reflects the world around us. We are an equal opportunity employer committed to unbiased hiring practices. All qualified applicants will receive consideration for employment without regard to race, religion, gender identity, disability, veteran status, or any other protected characteristic.
Why Join SunnyData?
Innovative Environment: Work with cutting-edge technologies and industry leaders in data engineering and AI.
Customer Impact: Make a real difference in how businesses leverage data for strategic decision-making.
Career Growth: Opportunities for professional development and career advancement.
Collaborative Culture: Join a supportive team that values collaboration and knowledge sharing.
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. Apply today and become a key player in SunnyData's success story.