Senior Data Architect
New
J
JobgetherIT Consulting
Remote work flexibility within the United States.Full-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 7+ years of experience in data architecture/engineering; 10+ years of consulting experience.
- Required Skills
- Cloud ComputingSparkCI/CDTerraformData modelingDatabricksMLOps
Requirements
- Bachelor’s degree in computer science, engineering, data-related fields, or equivalent professional experience.
- 7+ years of experience in data architecture, data engineering, analytics, performance optimization, pipeline integration, and infrastructure configuration.
- 10+ years of consulting experience delivering technology solutions for clients.
- Strong experience designing and implementing cloud data platforms using Azure, AWS, or GCP.
- Deep expertise in at least one major cloud ecosystem and working knowledge of additional cloud platforms.
- Advanced understanding of Lakehouse architecture, data warehouse design, data modeling, and modern data management practices.
- Hands-on experience with Databricks, Spark, Delta Lake, Iceberg, Hudi, and distributed computing environments.
- Strong knowledge of Spark Structured Streaming, Spark performance optimization, and cluster configuration.
- Experience designing and managing data pipelines using technologies such as Databricks Delta Live Tables and DBT.
- Understanding of MLOps concepts and experience supporting AI/ML model development and deployment workflows.
- Experience with Terraform, Git, CI/CD pipelines, automation, and integration testing.
- Ability to travel up to 15% as required.
Responsibilities
- Lead the architecture, design, and implementation of Lakehouse and data warehouse solutions within cloud-based environments.
- Translate business requirements into technical data strategies and scalable architecture designs.
- Collaborate with stakeholders to understand data needs and develop solutions aligned with business objectives.
- Establish and implement data governance frameworks, policies, and procedures to improve data management practices.
- Ensure data quality, integrity, security, and compliance through effective validation and monitoring processes.
- Design reusable, scalable data components and frameworks to support future analytics and AI initiatives.
- Lead and mentor data engineering teams, providing technical direction and architectural guidance.
- Develop cloud data solutions using platforms such as Azure, AWS, and GCP while following industry best practices.
- Troubleshoot, optimize, and maintain cloud data environments to improve performance, reliability, and scalability.
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