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AWS Databricks Architect (Full-Time, Remote)

Arkhya Tech. Inc. • United State
Remote
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AI Summary

Seeking an experienced AWS Databricks Architect to design and deliver scalable cloud-native data solutions. Responsibilities include architecting data lakehouses, ETL/ELT frameworks, and optimizing data platforms on AWS. Requires 8+ years in Data Engineering/Architecture and 3+ years with Databricks.

Key Highlights
Design and implement scalable data lakehouse architectures using Databricks on AWS.
Architect end-to-end data pipelines for batch and real-time processing.
Optimize data platform performance, scalability, security, and cost efficiency.
Key Responsibilities
Design and implement scalable data lakehouse architectures using Databricks on AWS.
Architect end-to-end data pipelines for batch and real-time data processing.
Collaborate with business stakeholders, data engineers, analysts, and application teams to define technical solutions.
Build robust ETL/ELT frameworks using Spark, PySpark, SQL, and Databricks.
Optimize data platform performance, scalability, security, and cost efficiency.
Establish data governance, security standards, and best practices.
Lead architecture reviews and provide technical guidance throughout the project lifecycle.
Mentor engineering teams and promote engineering best practices.
Technical Skills Required
Amazon Web Services Databricks Apache Spark
Benefits & Perks
100% Remote position
Competitive compensation
Long-term career growth
Nice to Have
Experience with Git, CI/CD, and Infrastructure as Code using Terraform or CloudFormation
AWS Solutions Architect Certification
Databricks Certified Professional Certification
Experience with Kafka or Amazon Kinesis
Previous experience working with enterprise or consulting clients

Job Description


We're Hiring: AWS Databricks Architect (Full-Time)


Location: Remote (West Coast, USA)

Employment Type: Full-Time


We are looking for an experienced AWS Databricks Architect to design and deliver scalable, cloud-native data solutions for enterprise clients. The ideal candidate will have strong expertise in AWS, Databricks, and modern data architecture, with the ability to lead technical discussions and drive end-to-end solution delivery.


Key Responsibilities

  • Design and implement scalable data lakehouse architectures using Databricks on AWS.
  • Architect end-to-end data pipelines for batch and real-time data processing.
  • Collaborate with business stakeholders, data engineers, analysts, and application teams to define technical solutions.
  • Build robust ETL/ELT frameworks using Spark, PySpark, SQL, and Databricks.
  • Optimize data platform performance, scalability, security, and cost efficiency.
  • Establish data governance, security standards, and best practices.
  • Lead architecture reviews and provide technical guidance throughout the project lifecycle.
  • Mentor engineering teams and promote engineering best practices.


Required Qualifications

  • 8+ years of experience in Data Engineering and Data Architecture.
  • 3+ years of hands-on experience with Databricks.
  • Strong experience designing and implementing solutions on AWS Cloud.
  • Expertise in Apache Spark, PySpark, SQL, and Delta Lake.
  • Experience with AWS services such as S3, Glue, Lambda, IAM, EMR, Redshift, Athena, and CloudWatch.
  • Strong understanding of Data Warehousing, Lakehouse Architecture, ETL/ELT, and Data Modeling.
  • Experience with Git, CI/CD, and Infrastructure as Code using Terraform or CloudFormation is preferred.
  • Excellent communication, leadership, and client-facing skills.


Preferred Qualifications

  • AWS Solutions Architect Certification.
  • Databricks Certified Professional Certification.
  • Experience with Kafka or Amazon Kinesis.
  • Previous experience working with enterprise or consulting clients.


Why Join Us?

  • Opportunity to work on large-scale cloud transformation initiatives.
  • 100% Remote position.
  • Collaborative and innovation-driven work environment.
  • Competitive compensation and long-term career growth.


How to Apply

Interested candidates can send their updated resume to:

[email protected]


We look forward to connecting with talented professionals who are passionate about building next-generation data platforms.


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