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Solutions Architect - Data Engineering & Databricks

sunnydata

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

Descripcion del puesto

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 solutions.

Key responsibilities

  • Design, build and deploy 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.
  • 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, and test data movement, transformation code and data components.

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.
  • Client-facing communication, presentation and documentation skills, including POCs, roadmaps, sequence diagrams and logical system views.
  • Preferred: experience leading teams, mentoring engineers and developing end-to-end production solutions.

Required skills

  • Data engineering technologies (Spark, Hadoop, Kafka), Databricks, and data science/ML 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 (Streamsets, Matillion, Fivetran, NiFi, AWS Data Migration Services, Azure Data Factory, IICS), dbt, Airflow, Luigi, and 2+ certifications such as Spark Associate or Data Engineer Associate.

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Source : ats:ashby

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Publicado hace 2 horas

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