Databricks
Databricks
Databricks izstrādā vienotu datu un mākslīgā intelekta platformu organizācijām, kurām nepieciešams pārvaldīt liela apjoma datus, veidot mašīnmācīšanās sistēmas un pārvērst analītiku ražošanas lietotnēs. Tās tehnoloģija apvieno datu inženieriju, Apache Spark apstrādi, analītiku un mašīnmācīšanās operācijas, palīdzot tehniskajām komandām strādāt visā datu dzīves ciklā — no apstrādes un eksperimentēšanas līdz ieviešanai un atziņu radīšanai.

Solutions Architect, Consumer Packaged Goods

Guide consumer packaged goods customers in shaping their data and AI strategies on Databricks. Design cloud-native architectures, accelerate adoption, and advise senior technical stakeholders.

Apraksts

  • Lead account technical strategy from discovery through production deployment and expanded platform use.
  • Design scalable, production-ready architectures for data engineering, machine learning and AI, and real-time analytics.
  • Advise customer architects, engineering leads, and directors on technical decisions.
  • Build tailored solutions that demonstrate Databricks’ strengths in competitive evaluations.
  • Establish a developing technical specialty and serve as a team resource in that area.
  • Coordinate data and solution architects, specialists, and partners to deliver end-to-end solutions.
  • Share structured customer feedback on requirements and competitive gaps to help shape product direction.
  • Take part in recruiter and hiring manager conversations, architecture reviews, live coding, solution demos and pitches, and reference checks.

Prasības

  • At least six years of experience in solutions architecture, data engineering, technical presales, or a senior hands-on technical role.
  • Strong Python and SQL coding skills, including live coding, debugging, and building solutions.
  • Deep knowledge of distributed data systems, scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms.
  • Proficiency with the Databricks Platform, or the ability to become proficient quickly.
  • A developing technical specialty in an area such as streaming and real-time data, machine learning and AI, data governance, or migrations.
  • Ability to lead architecture discussions with senior technical stakeholders through whiteboarding, design reviews, and trade-off analysis.
  • Experience deploying production workloads on AWS, Azure, or GCP, including infrastructure, security, and governance considerations.
  • A record of increasing platform adoption and usage within customer accounts.
  • Excellent communication skills for connecting complex architecture decisions to business value.
  • Bachelor’s or master’s degree in computer science, engineering, or a quantitative field, or equivalent experience.
  • Databricks certifications are a plus.
  • Experience with Snowflake, AWS native services, or Azure Synapse is a plus.
  • Experience at a data or AI company or cloud provider is a plus.
  • Industry domain expertise is a plus.

Priekšrocības

  • Eligible for an annual performance bonus.
  • Eligible for equity.
  • Comprehensive benefits and perks, with regional details available in Databricks benefits documentation.

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