Data Bricks Lead(Automotive)
local to client site; 4 days/wk+,TX/Dallas

Sr. Data Bricks Engineer
SQL
AWS

Do you have Sr. Data Bricks Engineer experience?
Will you work onsite at least 4x a week?

Mandatory Skills: Sr. Data Bricks Engineer, AWS, SQL

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
Design end-to-end data architectures using Databricks Lakehouse Platform.
Architect scalable ETL/ELT pipelines, real-time streaming solutions, and advanced analytics platforms.
Define data models, storage strategies, and integration patterns aligned with business and enterprise architecture standards.
Provide guidance on cluster configuration, performance optimization, cost management, and workspace governance.

2. Technical Leadership
Lead technical discussions and design workshops with engineering teams and business stakeholders.
Provide best practices, frameworks, and reusable component designs for consistent delivery.
Perform code reviews and provide technical mentoring to data engineers and developers.

3. Stakeholder & Project Engagement
Collaborate with product owners, business leaders, and analytics teams to translate business requirements into scalable technical solutions.
Create and present solution proposals, architectural diagrams, and implementation strategies.
Support pre-sales or discovery phases with technical input when needed.

4. Data Governance, Security & Compliance
Define and implement governance standards across Databricks workspaces (data lineage, cataloging, access control, etc.).
Ensure compliance with regulatory and organizational security frameworks.
Implement best practices for monitoring, auditing, and data quality management.

5. Continuous Improvement & Innovation
Stay updated on Databricks features, roadmap, and industry trends.
Recommend improvements, optimizations, and modernization opportunities across the data ecosystem.
Evaluate integration of complementary technologies (Delta Live Tables, MLflow, Unity Catalog, streaming frameworks, etc.).

Required Skills & Experience
Technical Skills
Databricks Expertise: Strong hands-on experience with Databricks (clusters, notebooks, Delta Lake, MLflow, Unity Catalog).
Cloud Platforms: Experience with at least one cloud provider (AWS, Azure, GCP).
Data Engineering: Strong proficiency in Spark, Python, SQL, and distributed data processing.
Architecture: Experience designing large-scale data solutions including ingestion, transformation, storage, and analytics.
Streaming: Experience with streaming technologies (Structured Streaming, Kafka, Kinesis, EventHub).
DevOps: CI/CD practices for data pipelines (Azure DevOps, GitHub Actions, Jenkins, etc.).

Soft Skills
Strong communication skills with the ability to engage both technical and business teams.
Experience working in Agile environments.
Ability to simplify complex technical concepts for non-technical audiences.
Strong analytical, problem-solving, and decision-making abilities.

Preferred Qualifications
Databricks Certified Data Engineer Professional / Architect certification.
AWS/Azure/GCP cloud architect certifications.
Experience with BI tools (Tableau, Power BI, Looker).
Experience in machine learning workflows and ML operations.
Background in large-scale data modernization or cloud migration projects.