Databricks Data Architect

Winfo Solutions; Atlanta (GA); Presencial; USD 150.000 - 190.000; Jornada completa

Descripción de la vacante

Winfo Solutions is seeking a full-time Data Architect/Databricks Solution Architect with a strong data engineering background. The role is on-site in the Atlanta and Dallas Metropolitan Area, focused on designing and delivering scalable data and AI platforms built on Databricks Lakehouse architecture.

You will lead architecture efforts, govern data solutions, and mentor engineering teams while partnering with stakeholders to drive digital transformation and analytics initiatives.

Formación

• 10+ years in software/data engineering or enterprise analytics.
• 3+ years hands-on Databricks Lakehouse Platform experience.

Responsabilidades

• Lead design and delivery of large-scale data and AI platforms.
• Define scalable, secure enterprise data solutions for analytics initiatives.
• Architect data models, integration patterns, and reference architectures.

Conocimientos

Data engineering

Databricks

Azure

Python

PySpark

SQL

Apache Spark

ETL/ELT

Data governance

IAM

Educación

Bachelor's/Master's in CS/IS/Engineering

Herramientas

Delta Lake

Unity Catalog

Databricks Workflows

Databricks SQL

Mlflow

Snowflake (preferred)

Descripción del empleo

Looking for full-time Data Architect/Databricks Solution Architect with strong Data Engineering background along with hands on Databricks and Azure skills, for on-site roles based in the Atlanta and Dallas Metropolitan Area. This role is responsible for leading the design and technical delivery of a large-scale data and AI platform implementation. This is a high-visibility, cross-technical role requiring someone who can build modern data and AI platforms built on the Databricks Lakehouse architecture, and for defining scalable, secure, and high-performing enterprise data solutions that accelerate digital transformation and analytics initiatives. The ideal candidate combines deep technical expertise with strong consulting and client-facing skills.

Key Responsibilities

• Collaborate with product teams, and data stewards to design and govern data solutions that ensure consistency, quality, and scalability across the Digital Experience ecosystem.
• Lead data architecture efforts that enable AI and automation adoption — identify enhancements, establish governance frameworks, and deliver scalable data foundations.
• Provide cross-product visibility by helping teams understand data impacts, integrations, and end-to-end data flows across Digital Experience systems and beyond.
• Evaluate new work intake for data architecture impact and develop high-level designs for initiatives that break new ground.
• Develop end-to-end enterprise data and analytics solutions using the Databricks Lakehouse Platform.
• Define scalable reference architectures, data models, integration patterns, and technology roadmaps aligned with business and enterprise architecture standards.
• Develop robust data ingestion, ETL/ELT, streaming, transformation, governance, and analytics solutions.
• Lead discovery workshops and collaborate with business stakeholders to gather functional and non-functional requirements.
• Guide implementation teams on best practices for Databricks, Apache Spark, Delta Lake, Unity Catalog, and cloud-native services.
• Design secure, governed, and cost-optimized data platforms with a focus on scalability, performance, and reliability.
• Integrate Databricks with enterprise applications, ERP platforms, APIs, cloud data services, and modern analytics ecosystems.
• Conduct architecture, design, and code reviews to ensure solution quality and adherence to enterprise standards.
• Optimize data pipelines, workloads, and infrastructure for performance and cost efficiency.
• Mentor data engineers and technical teams while promoting engineering excellence and architectural best practices.
• Create reusable frameworks, accelerators, reference implementations, and architectural assets that strengthen Data & AI offerings.
• Stay current with emerging Databricks capabilities, AI innovations, and cloud-native data engineering best practices.

Required Qualifications:

• Bachelor's or master's degree in computer science, Information Systems, Engineering, or related field.
• 10+ years of experience in software engineering, data engineering, data architecture, or enterprise analytics solution development.
• 3+ years of hands-on experience designing, developing, and implementing enterprise solutions on the Databricks Lakehouse Platform.
• Strong expertise with Databricks technologies, including Delta Lake, Unity Catalog, Databricks Workflows, Databricks SQL, and Mlflow. Advanced proficiency in Python, PySpark, SQL, and Apache Spark.
• Proven experience building scalable enterprise ETL/ELT pipelines, batch and streaming data processing solutions.
• Strong understanding of modern data architecture, data governance, metadata management, Unity Catalog, security, identity and access management (IAM), and regulatory compliance.
• Excellent communication, stakeholder management, and consulting skills, with the ability to translate business and technical requirements into scalable solution designs.

Preferred Qualifications:

• Databricks Certified Data Engineer Professional or Solution Architect certifications.
• Azure Developer or equivalent cloud certification.
• Working experience on Healthcare or Retail domain.
• Familiarity with Snowflake or any other equivalent data platform.