HMG America LLC is the best Business Solutions focused Information Technology Company with IT consulting and services, software and web development, staff augmentation and other professional services. One of our direct clients is looking for Databricks Architect in Remote. Below is the detailed job description.
We are seeking an experienced Databricks Architect to lead the design, development, and implementation of modern data engineering and analytics solutions on the Databricks platform. The ideal candidate will have deep expertise in cloud data architecture, strong experience building scalable data pipelines, and the ability to collaborate with cross-functional stakeholders to drive high-impact data initiatives.
Responsibilities
Architect and implement end-to-end data solutions on Databricks, including ingestion, ETL/ELT pipelines, data modeling, and optimization.
Build scalable and secure data architecture aligned with business and technology goals.
Design and optimize Delta Lake, Lakehouse architecture, and data governance frameworks.
Work closely with data engineers, analysts, and stakeholders to understand requirements and define technical roadmaps.
Lead migration of legacy pipelines to Databricks and modern cloud architectures.
Implement CI/CD, DevOps, and automation practices for data engineering workflows.
Optimize query performance, cluster configurations, and cost efficiency.
Ensure best-practices in security, data quality, and compliance across implementations.
Provide technical leadership, perform code reviews, and mentor engineering teams.
Collaborate with cloud architects to align Databricks solutions with enterprise cloud strategies.
Required Skills & Qualifications
15+ years of experience in Data Engineering / Data Architecture.
Strong hands-on experience with Databricks (SQL, PySpark, Workflows, Delta Lake, Unity Catalog).
Expertise in one or more cloud platforms: Azure, AWS, or Google Cloud Platform (Azure preferred).
Strong programming experience in Python, PySpark, SQL.
Experience designing Lakehouse architectures and modern data platforms.
Knowledge of ETL/ELT frameworks, DataOps, and CI/CD pipelines.
Proven experience building distributed data solutions at scale.
Familiarity with data governance, security models, and best practices.
Excellent communication skills with the ability to work with technical and non-technical teams.
Experience with MLflow, Feature Store, or machine learning pipelines.
Experience with real-time streaming (Kafka, Spark Structured Streaming).
Background in leading or mentoring engineering teams.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
Dice Id: 10481867
Position Id: 2025-16918
Posted 12 days ago
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