Senior Data Architect - Cloud Data Platform & Databricks

Interactive Resources - iR • Atlanta Metropolitan Area
Remote
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AI Summary

Lead design and development of cloud-native data platforms and pipelines for analytics and data science. Own architecture decisions across data lake, lakehouse, and pipeline design while mentoring engineers and setting technical direction. Establish standards for data modeling, ELT pipelines, orchestration, and performance tuning.

Key Highlights
Senior hands-on technical leadership role
Focus on Databricks, lakehouse architecture, and scalable data pipelines
Own architecture decisions and mentor team members
Key Responsibilities
Lead the design and development of cloud-native data platforms and pipelines for analytics and data science
Own architecture decisions across data lake, lakehouse, and pipeline design
Serve as a technical leader and mentor, guiding engineers through best practices and complex problem solving
Contribute hands on to Databricks development including notebooks, workflows, and optimization efforts
Establish standards for data modeling, ELT pipelines, orchestration, and performance tuning
Ensure data platforms are reliable, secure, and scalable
Partner with stakeholders to align technical solutions with business needs
Technical Skills Required
Azure Databricks Azure Data Lake Azure Fabric Azure Data Factory Databricks Distributed data processing frameworks Python PySpark SQL Lakehouse architecture Streaming pipelines Data mesh Data governance Data security Performance optimization
Benefits & Perks
Fully Remote
$175k annually

Job Description


Data Architect - Senior Data Engineer - Databricks

$175k annually

Fully Remote


This is a senior, hands-on technical leadership role focused on designing and building modern cloud data platforms. You will work closely with engineering, product, and business teams to deliver scalable data solutions that support analytics, reporting, and advanced data initiatives. This role is ideal for someone who enjoys owning architecture and implementation while guiding engineers and setting technical direction.

You will play a key role in shaping the evolution of a cloud-based data platform, with a strong focus on Databricks, lakehouse architecture, and scalable data pipelines. This is a highly visible role where you will influence best practices, mentor team members, and remain deeply involved in technical execution.

Responsibilities

  • Lead the design and development of cloud-native data platforms and pipelines for analytics and data science
  • Own architecture decisions across data lake, lakehouse, and pipeline design
  • Serve as a technical leader and mentor, guiding engineers through best practices and complex problem solving
  • Contribute hands on to Databricks development including notebooks, workflows, and optimization efforts
  • Establish standards for data modeling, ELT pipelines, orchestration, and performance tuning
  • Ensure data platforms are reliable, secure, and scalable
  • Partner with stakeholders to align technical solutions with business needs

Technical Experience

  • Strong experience with Azure data platforms including Azure Databricks, Data Lake, Fabric, and Data Factory
  • Deep hands on expertise in Databricks and distributed data processing frameworks
  • Proficiency in Python, PySpark, and SQL
  • Experience designing modern data architectures such as lakehouse, streaming pipelines, and data mesh
  • Strong understanding of data governance, security, and performance optimization


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