Databricks Data Architect
About The Position
We are seeking an experienced Databricks Data Architect to lead the design, development, and implementation of enterprise data architecture solutions using the Databricks Data Intelligence Platform. The role provides technical leadership in modern data architectures, including lakehouse solutions, data integration frameworks, data pipelines, and enterprise data management strategies. The architect works with business stakeholders, data engineers, cloud architects, and technical teams to translate business requirements into scalable data solutions that support organizational objectives. The successful candidate will bring expertise in Databricks, cloud data platforms, data modeling, data governance, and enterprise data architecture, and will guide technical decisions and data modernization initiatives. This is a hybrid position, with onsite work as needed based on client and business requirements. The role requires passing a federal background investigation before starting and maintaining eligibility throughout the engagement. The company is not currently sponsoring new H-1B visa petitions; applicants must be authorized to work in the United States without requiring new employer-sponsored H-1B sponsorship at this time.
Requirements
- At least 10 years of experience in data architecture, enterprise data management, or data engineering.
- Extensive hands-on experience designing and implementing enterprise data architectures using Databricks.
- Strong expertise with the Databricks Lakehouse Platform, including Delta Lake, Unity Catalog, and Delta Live Tables.
- Demonstrated experience designing and implementing scalable data pipelines and ETL/ELT processes.
- Strong knowledge of cloud-based data platforms, preferably AWS or Microsoft Azure.
- Experience with SQL, Python, and data processing frameworks such as Apache Spark and PySpark.
- Extensive experience with enterprise data modeling, data warehousing, data lakes, and lakehouse architectures.
- Experience developing data governance frameworks, metadata management, data lineage, and data quality strategies.
- Strong understanding of data security, access controls, encryption, and enterprise data protection practices.
- Experience with data integration tools, APIs, and structured and unstructured data sources.
- Ability to translate complex business and technical requirements into enterprise data architecture solutions.
- Strong analytical, problem-solving, communication, and technical leadership skills.
- Bachelor's degree in Computer Science, Information Technology, Data Engineering, Information Systems, or a related discipline; equivalent education and relevant professional experience may be considered.
- Must be able to pass a federal background investigation before starting work and maintain eligibility throughout the engagement.
- Must be authorized to work in the United States without requiring new employer-sponsored H-1B visa sponsorship at this time.
Nice To Haves
- Databricks Certified Data Engineer Professional or Databricks Certified Data Engineer Associate certification.
- Databricks Certified Data Architect certification.
- Experience supporting federal government agencies or large enterprise environments.
- Experience with AWS services such as S3, Glue, Redshift, Lambda, and IAM, or equivalent Azure services.
- Familiarity with data governance platforms such as Collibra.
- Experience with Power BI, Tableau, or other enterprise business intelligence platforms.
- Experience with machine learning, artificial intelligence, and generative AI data architecture.
- Experience leading cloud migration and enterprise data modernization initiatives.
- Familiarity with Agile development methodologies and DevSecOps practices.
- Master's degree.
Responsibilities
- Lead the design and implementation of enterprise data architectures using the Databricks Lakehouse Platform.
- Develop scalable, secure, high-performing data architecture solutions for enterprise analytics, reporting, and advanced data initiatives.
- Define data architecture standards, principles, reference architectures, and technical roadmaps.
- Architect and implement lakehouse solutions using Delta Lake, Delta Live Tables, Unity Catalog, and other Databricks capabilities.
- Design and oversee data integration, ingestion, transformation, and processing solutions using ETL/ELT frameworks.
- Establish enterprise data modeling strategies, including conceptual, logical, and physical data models.
- Design and optimize batch and streaming data pipelines for large-scale data processing.
- Provide architectural guidance for cloud data platforms, including AWS, Microsoft Azure, or Google Cloud.
- Establish data governance, data quality, metadata management, data lineage, and security frameworks.
- Implement data security and access control strategies, including role-based access controls and data protection standards.
- Collaborate with data engineers, data scientists, business analysts, and stakeholders to align architecture solutions with business and technical requirements.
- Evaluate data technologies and recommend solutions to improve scalability, performance, reliability, and cost efficiency.
- Lead technical reviews, architecture assessments, and design discussions to ensure compliance with enterprise standards and best practices.
- Identify opportunities to modernize legacy data environments and migrate existing platforms to Databricks.
- Provide technical mentorship and guidance to data engineering and development teams.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
