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RevStar

Databricks Forward Deployed Engineer

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeRemote in ColombiaNo salary listed

About the Job

Requirements

  • At least 5 years of hands-on experience in Data Engineering, Machine Learning, or Solutions Architecture.
  • At least 3 years of deep technical experience within the Databricks ecosystem, including Delta Lake, Unity Catalog, MLflow, Spark/PySpark, Databricks Workflows/Jobs, and Mosaic AI.
  • Practical experience designing and deploying retrieval-augmented generation pipelines, fine-tuning large language models, working with vector databases, and managing machine-learning pipelines end-to-end.
  • Strong expertise in cloud-native architectures; AWS experience is preferred, including S3, Glue, Lambda, and Redshift.
  • A proven track record of migrating enterprise legacy data warehouses or lakes onto Databricks.
  • A demonstrated track record of leading technical delivery for Fortune 500 or large enterprise clients.
  • Experience presenting technical architecture, building proofs of concept and demos, and managing client stakeholders up to the C-suite.
  • Ability to identify technical expansion opportunities within existing client accounts and serve as a technical advocate to grow account footprint.
  • Exceptional verbal and written communication skills.

Responsibilities

  • Design, build, and deploy production-grade data pipelines, analytics engines, and generative AI/large language model applications using Databricks, Spark, Python/PySpark, and modern cloud ecosystems including AWS, Azure, and GCP.
  • Serve as the primary technical leader on strategic enterprise client engagements, partnering with C-level executives, data leaders, and engineering teams to translate business challenges into technical solutions.
  • Lead complex migrations of legacy platforms, including Snowflake, Teradata, legacy Hadoop, and SQL Server, onto Databricks Lakehouse architecture.
  • Guide enterprise customers in adopting generative AI solutions, retrieval-augmented generation architectures, model fine-tuning, and MLflow/Databricks Mosaic AI integrations.
  • Partner with account leadership to identify high-value technical use cases across client business units, expanding Databricks platform usage and driving measurable client return on investment.
  • Mentor and coach junior solution engineers, architects, and consultants.
  • Contribute to internal code libraries, reusable accelerators, and technical delivery best practices.

Desired Qualifications

  • Databricks Certified Data Engineer Professional certification and/or Machine Learning Professional certification.
  • Experience in healthcare, retail, or consumer goods.

About the Company

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