Senior Azure Data Engineer

Data Engineer

Client: CFI (College Foundation Inc)

Location: Local to NC -- anywhere in NC is okay

Rate: $75/hr W2

Need LinkedIn

Will be mostly remote with 1 day onsite per month

Top Skills:

• Extensive Azure SQL Server experience--optimizing table, creating indexes, use analytics to set access, script creation
• Azure Data Lakes--converting from source to another
• Azure Data Factory--move data btw sources using ETL
• Data Modeling
• Experience working in a Greenfield environment

Project: working on multiple projects to optimize SQL Server schema, entire Data Modeling and Analytics of greenfield, ETL, taking documents & extracting data for reports, etc.

Qualifications Required Bachelor's degree in Computer Science, Engineering, Data Science, or a related quantitative field, or equivalent practical experience. 5+ years of progressive experience in data engineering, with a strong portfolio demonstrating expertise in building and managing large-scale data solutions. Proficiency in at least one major programming language used for data engineering (e.g., Python, Scala, Java). Extensive experience with modern data warehousing and/or data lake technologies (e.g., Snowflake, Databricks, Google BigQuery, Azure Synapse/Data Lake, AWS Redshift). Demonstrated experience designing and implementing ETL/ELT pipelines using various tools and frameworks. Strong understanding of data modeling principles, database design (relational and NoSQL), and SQL optimization. Deep experience with Microsoft Azure cloud services including data-related services. Excellent problem-solving, analytical, and critical thinking skills. Strong written and verbal communication skills, with the ability to articulate technical concepts to diverse audiences. Proven ability to be self-driven, adaptable, and manage multiple priorities in a fast-paced environment. Prior experience in a consulting or client-facing role. Preferred Familiarity with streaming data technologies (e.g., Apache Kafka, AWS Kinesis, Google Pub/Sub). Experience implementing DataOps principles and CI/CD pipelines for data solutions. Knowledge of data governance, metadata management, and data lineage tools. Experience with business intelligence tools (e.g., Tableau, Power BI, Looker).