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Solutions Architect - Databricks

SunnyData

New
Senior 🇬🇧 English
Databricks Apache Spark Hadoop Kafka AWS Azure GCP Java Python Scala SQL dbt Airflow NiFi Matillion Fivetran

Job description

About the role

SunnyData, a Databricks technology partner, is looking for a Solutions Architect to drive customer success through technical execution and pre-sales support. The role splits time evenly between billable work and pre-sales activities, advising customers on their data engineering and data architecture needs with a focus on Databricks.

Key responsibilities

  • Act as a trusted advisor to customers, guiding them through data engineering and data architecture needs.
  • Design, build and deploy data solutions that support AI, ML and business intelligence initiatives.
  • Collaborate with sales teams to present technical solutions to prospective clients.
  • Manage multiple customer accounts, track progress and report outcomes.
  • Architect data solutions with best practices in data governance, security and quality.
  • Evaluate data sources and recommend data inclusion strategies.
  • Lead internal teams, mentor project teams and educate end users on data products and analytic environments.
  • Analyze and resolve data and system defects, test data movement, transformation code and components, and write detailed solution documentation including POCs, roadmaps, sequence diagrams and logical system views.

Required profile

  • 7+ years as a hands-on Solutions Architect and/or Senior Data Engineer, with more recent experience implementing data solutions focused on Databricks.
  • Bachelor's degree in Computer Science or a related engineering field.
  • Ability to lead complex architecture requirements, design sessions and implementation blueprints.
  • Strong written and verbal communication, presentation and client-facing skills.
  • Preferred: experience leading teams and mentoring engineers.

Required skills

  • Data engineering technologies (Spark, Hadoop, Kafka), Databricks, and data science / machine learning tools (pandas, scikit-learn).
  • Java, Python and/or Scala; SQL writing, debugging and optimization.
  • Cloud platforms: AWS, Azure and/or GCP.
  • Preferred: distributed storage (S3, ADLS, HDFS, GCS, Kudu, Elasticsearch/Solr, Cassandra), data integration tools (Streamsets, Matillion, Fivetran, NiFi, Airflow, dbt), and certifications such as Spark Associate or Data Engineer Associate.

Questions fréquentes

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Published 5 days ago

Expires 1 month from now

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