

Net2Source Inc.
Databricks Architect
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Databricks Architect in Dallas, TX, offering a contract length of "unknown" at a pay rate of "unknown." Key skills include Databricks, AWS, SQL, and experience in data architecture and engineering. Certifications in Databricks and cloud platforms are preferred.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
Unknown
-
ποΈ - Date
August 13, 2026
π - Duration
Unknown
-
ποΈ - Location
Unknown
-
π - Contract
Unknown
-
π - Security
Unknown
-
π - Location detailed
Dallas, TX
-
π§ - Skills detailed
#Data Quality #Security #Tableau #Storage #Scala #Compliance #BI (Business Intelligence) #Azure DevOps #Databricks #MLflow #Jenkins #Data Engineering #Kafka (Apache Kafka) #GCP (Google Cloud Platform) #Spark (Apache Spark) #Agile #Looker #ML (Machine Learning) #Monitoring #AWS (Amazon Web Services) #Data Pipeline #SQL (Structured Query Language) #Delta Lake #"ETL (Extract #Transform #Load)" #Code Reviews #Microsoft Power BI #Data Governance #Data Bricks #Data Architecture #Migration #DevOps #Python #Data Processing #GitHub #Leadership #Data Lineage #Azure #Cloud
Role description
Title: Sr. Data Bricks Engineer/ Architect
Mandatory Skills: Sr. Data Bricks Engineer, AWS, SQL
City: Dallas
State: TX
Role Description
Role Summary
We are looking for a highly skilled Databricks Solution Architect to lead the design and implementation of scalable, enterprise-grade data platforms using Databricks. The ideal candidate will combine strong technical expertise in data engineering and cloud platforms (AWS/Azure/GCP) with architectural leadership, solution design capability, and strong stakeholder engagement skills.
Key Responsibilities
1. Solution Architecture & Design
β’ Design end-to-end data architectures using Databricks Lakehouse Platform.
β’ Architect scalable ETL/ELT pipelines, real-time streaming solutions, and advanced analytics platforms.
β’ Define data models, storage strategies, and integration patterns aligned with business and enterprise architecture standards.
β’ Provide guidance on cluster configuration, performance optimization, cost management, and workspace governance.
1. Technical Leadership
β’ Lead technical discussions and design workshops with engineering teams and business stakeholders.
β’ Provide best practices, frameworks, and reusable component designs for consistent delivery.
β’ Perform code reviews and provide technical mentoring to data engineers and developers.
1. Stakeholder & Project Engagement
β’ Collaborate with product owners, business leaders, and analytics teams to translate business requirements into scalable technical solutions.
β’ Create and present solution proposals, architectural diagrams, and implementation strategies.
β’ Support pre-sales or discovery phases with technical input when needed.
1. Data Governance, Security & Compliance
β’ Define and implement governance standards across Databricks workspaces (data lineage, cataloging, access control, etc.).
β’ Ensure compliance with regulatory and organizational security frameworks.
β’ Implement best practices for monitoring, auditing, and data quality management.
1. Continuous Improvement & Innovation
β’ Stay updated on Databricks features, roadmap, and industry trends.
β’ Recommend improvements, optimizations, and modernization opportunities across the data ecosystem.
β’ Evaluate integration of complementary technologies (Delta Live Tables, MLflow, Unity Catalog, streaming frameworks, etc.)
Required Skills & Experience:
Technical Skills
β’ Strong hands-on experience with Databricks (clusters, notebooks, Delta Lake, MLflow, Unity Catalog).
β’ Experience with at least one cloud provider (AWS, Azure, GCP).
β’ Strong proficiency in Spark, Python, SQL, and distributed data processing.
β’ Experience designing large-scale data solutions (ingestion, transformation, storage, analytics).
β’ Experience with streaming technologies (Structured Streaming, Kafka, Kinesis, EventHub).
β’ CI/CD practices for data pipelines (Azure DevOps, GitHub Actions, Jenkins, etc.).
Soft Skills
β’ Strong communication skills with ability to engage technical and business teams.
β’ Experience working in Agile environments.
β’ Ability to simplify complex technical concepts for non-technical audiences.
β’ Strong analytical, problem-solving, and decision-making abilities.
Preferred Qualifications
β’ Databricks Certified Data Engineer Professional / Architect certification.
β’ AWS/Azure/GCP cloud architect certifications.
β’ Experience with BI tools (Tableau, Power BI, Looker).
β’ Experience in machine learning workflows and ML operations.
β’ Background in large-scale data modernization or cloud migration projects.
Title: Sr. Data Bricks Engineer/ Architect
Mandatory Skills: Sr. Data Bricks Engineer, AWS, SQL
City: Dallas
State: TX
Role Description
Role Summary
We are looking for a highly skilled Databricks Solution Architect to lead the design and implementation of scalable, enterprise-grade data platforms using Databricks. The ideal candidate will combine strong technical expertise in data engineering and cloud platforms (AWS/Azure/GCP) with architectural leadership, solution design capability, and strong stakeholder engagement skills.
Key Responsibilities
1. Solution Architecture & Design
β’ Design end-to-end data architectures using Databricks Lakehouse Platform.
β’ Architect scalable ETL/ELT pipelines, real-time streaming solutions, and advanced analytics platforms.
β’ Define data models, storage strategies, and integration patterns aligned with business and enterprise architecture standards.
β’ Provide guidance on cluster configuration, performance optimization, cost management, and workspace governance.
1. Technical Leadership
β’ Lead technical discussions and design workshops with engineering teams and business stakeholders.
β’ Provide best practices, frameworks, and reusable component designs for consistent delivery.
β’ Perform code reviews and provide technical mentoring to data engineers and developers.
1. Stakeholder & Project Engagement
β’ Collaborate with product owners, business leaders, and analytics teams to translate business requirements into scalable technical solutions.
β’ Create and present solution proposals, architectural diagrams, and implementation strategies.
β’ Support pre-sales or discovery phases with technical input when needed.
1. Data Governance, Security & Compliance
β’ Define and implement governance standards across Databricks workspaces (data lineage, cataloging, access control, etc.).
β’ Ensure compliance with regulatory and organizational security frameworks.
β’ Implement best practices for monitoring, auditing, and data quality management.
1. Continuous Improvement & Innovation
β’ Stay updated on Databricks features, roadmap, and industry trends.
β’ Recommend improvements, optimizations, and modernization opportunities across the data ecosystem.
β’ Evaluate integration of complementary technologies (Delta Live Tables, MLflow, Unity Catalog, streaming frameworks, etc.)
Required Skills & Experience:
Technical Skills
β’ Strong hands-on experience with Databricks (clusters, notebooks, Delta Lake, MLflow, Unity Catalog).
β’ Experience with at least one cloud provider (AWS, Azure, GCP).
β’ Strong proficiency in Spark, Python, SQL, and distributed data processing.
β’ Experience designing large-scale data solutions (ingestion, transformation, storage, analytics).
β’ Experience with streaming technologies (Structured Streaming, Kafka, Kinesis, EventHub).
β’ CI/CD practices for data pipelines (Azure DevOps, GitHub Actions, Jenkins, etc.).
Soft Skills
β’ Strong communication skills with ability to engage technical and business teams.
β’ Experience working in Agile environments.
β’ Ability to simplify complex technical concepts for non-technical audiences.
β’ Strong analytical, problem-solving, and decision-making abilities.
Preferred Qualifications
β’ Databricks Certified Data Engineer Professional / Architect certification.
β’ AWS/Azure/GCP cloud architect certifications.
β’ Experience with BI tools (Tableau, Power BI, Looker).
β’ Experience in machine learning workflows and ML operations.
β’ Background in large-scale data modernization or cloud migration projects.






