Databricks Data Engineer II
- Design, build, and maintain data pipelines and data engineering solutions using Databricks, Apache Spark, Python, and Structured Query Language (SQL)
- Support the modernization of enterprise data platforms by implementing cloud-based ingestion, transformation, and storage patterns
- Develop and maintain batch and streaming data workflows that support reporting, analytics, and artificial intelligence use cases
- Apply data architecture, integration, and data modeling practices to improve data quality, scalability, and platform performance
- Collaborate with client and Deloitte teams to troubleshoot issues, implement enhancements, and support delivery of large-scale data transformation programs
- Ability to work independently and collaborate as part of a team
- Effective written and verbal communication skills
- Meticulous attention to detail and quality of work product
- Ability to build and sustain professional relationships
- Ability to lead projects or workstreams
- Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
- Strong interpersonal skills and professional demeanor
- Ability to meet deadlines
- Ability to provide clear guidance to others
- Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, Mathematics, or Statistics
- 3+ years of experience in data engineering, extract, transform, load (ETL) development, or data platform engineering
- 2+ years of experience building data pipelines in Databricks using Apache Spark, Python, and Structured Query Language (SQL)
- Experience implementing data models, data integration patterns, and cloud-based data processing workflows
- Experience working with at least one cloud platform: Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP)
- Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
- Limited immigration sponsorship may be available.
- Experience with Delta Lake, Databricks Workflows, and Unity Catalog
- Experience using Git-based version control and continuous integration/continuous deployment pipelines
- Experience supporting batch and streaming data workloads
- Experience with data warehousing, lakehouse architecture, and performance optimization
- Experience supporting analytics or machine learning data pipelines
- Experience working in consulting or client service delivery environments
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