Role: Senior Azure Data Engineer-W2
Location: Local to NC -- anywhere in NC is okay
**Will be mostly remote with 1 day onsite per month**
Top Skills:
1. Extensive Azure SQL Server experience--optimizing table, creating indexes, use analytics to set access, script creation
2. Azure Data Lakes--converting from source to another
3. Azure Data Factory--move data btw sources using ETL
4. Data Modeling
5. 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).
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