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Databricks Lead/Architect

Sysintelli, Inc.Tysons, VA🇺🇸United StatesPosted 7 Aug 2026

Why This Role Stands Out

This hybrid Databricks Lead/Architect role offers a fantastic opportunity to shape enterprise data platforms and mentor a growing team within a reputable company. You’ll thrive here if you possess strong data architecture and governance skills, enjoy collaborative problem-solving, and are eager to advance your expertise in cutting-edge data technologies. Apply now to lead impactful data solutions and unlock your career potential.

Quick Overview

Work Type
Hybrid
Level
Mid Senior

Job Description

Databricks Lead/Architect

Introduction:

As a Databricks Lead/Architect, you will be responsible for designing, implementing, and governing enterprise Data Platform. You will play a crucial role in leading the team towards successful data management and analysis.

Responsibilities:

  • Design and develop data architecture solutions using Databricks platform.
  • Lead the implementation of Databricks platform for data processing and analytics.
  • Govern the data platform to ensure data quality, security, and compliance.
  • Collaborate with cross-functional teams to understand business requirements and provide technical solutions.
  • Optimize and tune Databricks applications for performance and scalability.
  • Provide technical guidance and mentorship to junior team members.
  • Stay updated with the latest technologies and trends in data management and analysis.

Requirements:

Required Skills:

  • Proven experience as a Databricks Lead/Architect in designing and implementing enterprise Data Platform.
  • Strong knowledge of Databricks platform and its capabilities.
  • Hands-on experience in data architecture design and development.
  • Excellent understanding of data governance principles.
  • Ability to work effectively in a team environment and collaborate with stakeholders.

Preferred Skills:

  • Certification in Databricks or related technologies.
  • Experience in cloud-based data platforms such as AWS, Azure, or Google Cloud Platform.
  • Knowledge of big data technologies like Hadoop, Spark, and Kafka.
  • Experience in building machine learning models and data pipelines.

Skills

AWS
Machine Learning
Azure
Compliance
Databricks
Google Cloud
Hadoop
Kafka

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