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SunnyData

Data Solutions Architect (Financial Services)

RemoteUnited States only
Published
Role
Data Engineering
Experience
Senior
Employment
Full-time
Salary not disclosed
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Open to US only. Set where you work from to check your eligibility.

No BS summary

Solutions Architect with 7+ years of experience in data engineering and Databricks, focusing on designing and implementing scalable data solutions. Must have expertise in Spark, Hadoop, Kafka, Databricks, cloud platforms (AWS, Azure, GCP), and SQL, with strong client-facing and leadership skills. Experience in Financial Services is preferred.

Core skills

DatabricksData ArchitectureData Engineering

Required skills

SparkHadoopKafkapandasscikit-learnJavaPythonScalaAWSAzureGCPSQL

Optional skills

S3ADLSHDFSGCSKuduElasticsearchSolrCassandra

Required languages

English

What you'll do

  • Serve as a trusted advisor to customers, guiding them through their data engineering and data architecture needs with a focus on Databricks solutions.
  • Split your time evenly between billable and pre-sales activity.
  • Design, build, and deploy comprehensive data solutions that capture, transform, and leverage data to support AI, ML, and business intelligence initiatives.
  • Collaborate with sales teams to present technical solutions to prospective clients, demonstrating the value of SunnyData's offerings.
  • Manage multiple customer accounts, ensuring timely delivery of solutions and tracking progress to report outcomes.
  • Architect data solutions, incorporating best practices in data governance, security, and quality.
  • 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.
  • Test data movement, transformation code, and data components to ensure accuracy and reliability.

What they require

  • 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.
  • AWS, Azure, and/or GCP.
  • Ability to write, debug, and optimize SQL queries.
  • Strong written and verbal communication skills with experience in client-facing roles.
  • Ability to create and deliver detailed presentations to clients and stakeholders.
  • Experience in creating detailed solution documentation including POCs, roadmaps, sequence diagrams, class hierarchies, and logical system views.
  • Experience leading teams and mentoring other engineers.
  • Ability to develop end-to-end technical solutions into production, ensuring performance, security, scalability, and robust data integration.
  • Preferred Experience: Familiarity with cloud and distributed data storage systems such as S3, ADLS, HDFS, GCS, Kudu, ElasticSearch/Solr, Cassandra, or other NoSQL storage systems.
  • Preferred Experience: Experience with data integration technologies like Spark, Kafka, Streamsets, Matillion, Fivetran, NiFi, AWS Data Migration Services, Azure DataFactory, and Informatica Intelligent Cloud Services (IICS).
  • Preferred Experience: Comprehensive experience with the complete software development lifecycle including design, documentation, implementation, testing, and deployment.
  • Preferred Experience: Expertise in automated data transformation and curation using tools like dbt, Spark, Spark streaming, and automated pipelines.
  • Preferred Experience: Experience with workflow management and orchestration tools like Airflow, AWS Managed Airflow, Luigi, and NiFi.
  • Preferred Experience: Background working in the Financial Services industry, preferably in a banking environment.
  • Preferred Experience: Understand industry compliance requirements and standards, specifically in banking IT landscapes
  • Preferred Experience: 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: 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 15 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.

SunnyData is a leading DataBricks technology partner whose mission is to empower customers with scalable architectures, robust data engineering pipelines, seamless data consumption layers, and advanced ML and AI applications.

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