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RevStar
RevStar
51 – 200 Darbinieki
B2BKonsultācijasMākslīgais intelekts
RevStar is a digital transformation consultancy that helps organizations turn strategic priorities into working products and services. Its team brings together growth planning, customer journey design, AI and generative AI planning, data infrastructure, product testing, MVP development, and technology modernization. RevStar works with leaders in healthcare, insurance, and finance on mission-critical challenges, connecting strategic direction with hands-on technical execution. The company’s hiring context is not specified in the available information.
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Vakances uzņēmumā

Remote Data and AI Engineer

Build cloud-agnostic Databricks Lakehouse pipelines and production AI solutions as RevStar’s Data and AI Engineer. Create scalable data architectures, MLOps workflows, and governance practices, and hand off solutions to client teams.

USAmerikas Savienotās ValstisAZArizonaFLFloridaILIlinoisaIAAiovaMEMeinaNJŅūdžersijaNYŅujorkaSCDienvidkarolīnaTXTeksasaVAVirdžīnijaAttālinātiPilna slodzeVidējais līmenisVecākais speciālistsNepieciešamā Valoda: angļuMākslīgā intelekta inženierisMašīnmācīšanās inženieris
ApacheAWSAzureETLGoogle Cloud PlatformMākonisPythonSparkSQLTerraformUnity

Apraksts

  • Build and optimize ETL/ELT pipelines with Apache Spark and Delta Lake across AWS, Azure, and GCP.
  • Create Lakehouse architectures for structured and unstructured enterprise data.
  • Automate data ingestion, storage, and feature engineering for analytics and real-time AI workloads.
  • Optimize Spark jobs for low latency, high throughput, and efficient cloud spending.
  • Work with ML engineers and data scientists to deploy AI models in Databricks using MLflow.
  • Build CI/CD pipelines and infrastructure as code with Terraform and the Databricks CLI.
  • Apply enterprise security, access controls, and GDPR, HIPAA, and SOC 2 compliance standards in Unity Catalog and cloud environments.
  • Work with client technology leaders, product managers, and engineering teams to turn AI data needs into business outcomes.
  • Write technical documentation and lead solution handoffs to client engineering teams.
  • Report to the Product Manager or Engineering Lead.

Prasības

  • At least 3 years of cloud-native data engineering experience.
  • At least 2 years of hands-on experience with Databricks, Apache Spark, Delta Lake, and MLflow.
  • Strong skills in Python, SQL, Spark frameworks, CI/CD, and infrastructure as code using Terraform or the Databricks CLI.
  • An active Databricks Certified Data Engineer (Associate or Professional) or Databricks ML Professional certification is strongly preferred.
  • Experience working in fast-paced Agile and DevOps consulting environments.
  • Experience delivering cloud-agnostic architectures.
  • Excellent client communication skills.
  • Must meet U.S. work authorization requirements for direct W-2 employment through E-Verify.

Priekšrocības

  • Paid time off to recharge.
  • Remote-first work with a globally connected team.
  • Medical, dental, and vision coverage.
  • Company-sponsored 401(k) retirement plan.
  • Annual stipend for learning and development, including conferences, certifications, and courses.
  • Peer mentorship and coaching from experienced engineers, product managers, and architects.
  • Professional growth through exposure to AWS generative AI, data, and cloud technologies across industries.
  • Company outings and volunteer opportunities.
  • A collaborative, innovative workplace that values curiosity and initiative.

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