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Databricks Architect

SIGNin Solutions Inc.New York, NY🇺🇸United StatesPosted 15 Sept 2026

Why This Role Stands Out

This hybrid Databricks Architect role offers a fantastic opportunity to shape cutting-edge data platforms using Databricks and cloud technologies, empowering you to drive significant impact. You'll thrive here if you're an experienced data architect with a passion for building scalable solutions and optimizing performance, collaborating with talented teams to unlock data's full potential. Apply today to join SIGNin Solutions Inc. and advance your career in a dynamic environment.

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
New York, NY, United States
Posted
22 hours ago
SQLAWSETLApacheApache SparkAzureDatabricksGitGoogle CloudJenkins

Job Description

Databricks Architect

Job Summary

We are looking for an experienced Databricks Architect to design and implement scalable data platforms using Databricks, Apache Spark, and cloud technologies. The candidate will work with data engineering teams to build reliable data pipelines, data lakes, and analytics solutions.

Responsibilities
  • Design and implement Databricks data architecture and data platforms.
  • Develop and optimize ETL/ELT pipelines using Databricks and Apache Spark.
  • Work with Delta Lake, PySpark, SQL, and Databricks Workflows.
  • Design Data Lake / Lakehouse solutions on AWS, Azure, or Google Cloud Platform.
  • Implement data ingestion from various sources into Databricks.
  • Optimize Spark jobs, clusters, queries, and overall platform performance.
  • Implement data security, governance, access control, and monitoring.
  • Work with cloud services such as Azure Data Lake, AWS S3, or Google Cloud Platform Cloud Storage.
  • Collaborate with Data Engineers, Data Scientists, Analysts, and business teams.
  • Provide technical guidance and architecture best practices to the development team.
Required Skills
  • 8+ years of experience in Data Engineering / Data Architecture.
  • Strong hands-on experience with Databricks.
  • Strong knowledge of Apache Spark / PySpark.
  • Experience with Delta Lake and Lakehouse architecture.
  • Strong SQL and data modeling skills.
  • Experience with AWS, Azure, or Google Cloud Platform.
  • Experience designing scalable ETL/ELT data pipelines.
  • Knowledge of data security, governance, and performance tuning.
  • Experience with CI/CD and tools such as Git, Azure DevOps, or Jenkins.
  • Good communication and architecture/design skills.

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