Data Engineer ( Data Bricks)

  • San Jose, CA
  • Posted 12 hours ago | Updated 12 hours ago

Overview

Hybrid
$60 - $70
Contract - Independent
Contract - W2
Contract - 6 Month(s)

Skills

Apache Spark
Data Engineering
Databricks
Data Governance
Data Modeling
Generative Artificial Intelligence (AI)
Extract
Transform
Load
Microsoft Power BI
SQL
Master Data Management
Data Structure
Dashboard
Analytics
Amazon Web Services
Workflow
Data Quality
Python
Use Cases
Microsoft Azure
Business Intelligence

Job Details

Required Qualifications:

  • Extensive hands-on experience with Databricks (Spark, Delta Lake, Lakehouse architecture, notebooks, orchestration).
  • 3+ years of experience in data engineering, full-stack development, or a related field.
  • Strong proficiency in SQL and data modeling best practices.
  • Solid understanding of customer data structures, MDM concepts, and data governance.
  • Experience working with generative AI and LLMs, including prompt engineering and AI-assisted workflows.
  • Experience developing and deploying custom applications, APIs, or internal tools.
  • Proficiency in cloud environments (Azure, AWS, or Google Cloud Platform).

Key Responsibilities:

  • Design, develop, and optimize advanced data pipelines using Databricks (SQL, Python, Spark, Delta Lake).
  • Integrate and structure customer and enterprise data across systems to support analytics, AI, and MDM initiatives.
  • Build and maintain custom internal applications and services that support data workflows and operational teams.
  • Develop and refine prompts and workflows for LLM-based and generative AI use cases.
  • Collaborate with MDM teams to support identity resolution and golden record management.
  • Enable analytics delivery through Power BI, Tableau, and other BI tools.
  • Replicate data from sources to targets via Fivetran
  • Use reverse ETL tools like Census to replicate enriched data back into CRM and marketing systems.
  • Apply user experience design principles to internal data tools, dashboards, and interfaces to improve usability and adoption.
  • Ensure high data quality, reliability, and performance across the data stack.
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About RIIASH LLC