Role: Senior Data Engineer
Location: Atlanta, GA
Contract
Primary Skills
Data Modelling Fundamentals, Data Warehousing, ETL Fundamentals, Modern Data Platform Fundamentals, PLSQL, T-SQL, Stored Procedures, Python, Snowflake Data Exchange, Snowpipe, SnowSQL, SQL, SQL (Basic + Advanced), Time Travel and Fail Safe, Zero Copy Cloning
Secondary Skills
- Azure, AI/ML
- Specialization
- Snowflake Data Architecture: Lead Data Engineer
The ideal candidate will have extensive expertise in data engineering, with a focus on data warehousing, Snowflake, streaming data pipelines, Kafka, Debezium, BI and reporting tools, embedded reporting, and ETL processes. This role will involve designing, implementing, and optimizing scalable data solutions to support business intelligence, analytics, and AI/ML needs.
Key Responsibilities
- Data Pipeline Development: Design, build, and maintain robust ETL/ELT pipelines for efficient data ingestion, transformation, and integration from diverse sources.
- Data Warehousing: Architect and optimize data warehouse solutions using Snowflake, ensuring scalability, performance, and reliability.
- Streaming Data Pipelines: Develop and manage real-time data streaming pipelines using technologies such as Kafka and Debezium.
- ERP Integration: Collaborate with ERP system teams to ensure seamless integration of enterprise data into the data ecosystem. Understand SSO, embedded reporting scenarios.
- BI and Reporting: Work with BI tools (e.g., OAS, Domo, etc) to enable embedded reporting solutions and provide actionable insights.
- Data Modeling: Design scalable data models (e.g., star schema, snowflake schema) to support analytics and reporting needs.
- Collaboration: Partner with cross-functional teams including to understand requirements and deliver tailored solutions.
- System Monitoring & Optimization: Monitor system performance, troubleshoot issues, and implement optimizations to enhance efficiency.
- Required Skills & Qualifications Technical Expertise:
- Proficiency in Snowflake architecture and SQL for complex queries.
- Hands-on experience with Kafka for real-time data streaming.
- Familiarity with cloud platforms such as AWS and Azure.
- Knowledge of ERP systems integration.
Data Engineering Skills:
- Expertise in data modeling techniques (e.g., star schema, snowflake schema).
- Solid understanding of access control mechanisms and SSO protocols.
- Experience in designing scalable ETL/ELT pipelines.
- Soft Skills:
- Strong problem-solving abilities in ambiguous environments.
- Excellent communication skills for collaborating across teams.
- Preferred Qualifications
- Bachelor s or Master s degree in Computer Science, Engineering, or a related field.
- Experience migrating on-premise systems to cloud-based platforms.
- Familiarity with modern CI/CD pipelines for deployment automation.
Role: Senior Data Engineer
Location: Atlanta, GA
Contract
Primary Skills
Data Modelling Fundamentals, Data Warehousing, ETL Fundamentals, Modern Data Platform Fundamentals, PLSQL, T-SQL, Stored Procedures, Python, Snowflake Data Exchange, Snowpipe, SnowSQL, SQL, SQL (Basic + Advanced), Time Travel and Fail Safe, Zero Copy Cloning
Secondary Skills
- Azure, AI/ML
- Specialization
- Snowflake Data Architecture: Lead Data Engineer
The ideal candidate will have extensive expertise in data engineering, with a focus on data warehousing, Snowflake, streaming data pipelines, Kafka, Debezium, BI and reporting tools, embedded reporting, and ETL processes. This role will involve designing, implementing, and optimizing scalable data solutions to support business intelligence, analytics, and AI/ML needs.
Key Responsibilities
- Data Pipeline Development: Design, build, and maintain robust ETL/ELT pipelines for efficient data ingestion, transformation, and integration from diverse sources.
- Data Warehousing: Architect and optimize data warehouse solutions using Snowflake, ensuring scalability, performance, and reliability.
- Streaming Data Pipelines: Develop and manage real-time data streaming pipelines using technologies such as Kafka and Debezium.
- ERP Integration: Collaborate with ERP system teams to ensure seamless integration of enterprise data into the data ecosystem. Understand SSO, embedded reporting scenarios.
- BI and Reporting: Work with BI tools (e.g., OAS, Domo, etc) to enable embedded reporting solutions and provide actionable insights.
- Data Modeling: Design scalable data models (e.g., star schema, snowflake schema) to support analytics and reporting needs.
- Collaboration: Partner with cross-functional teams including to understand requirements and deliver tailored solutions.
- System Monitoring & Optimization: Monitor system performance, troubleshoot issues, and implement optimizations to enhance efficiency.
- Required Skills & Qualifications Technical Expertise:
- Proficiency in Snowflake architecture and SQL for complex queries.
- Hands-on experience with Kafka for real-time data streaming.
- Familiarity with cloud platforms such as AWS and Azure.
- Knowledge of ERP systems integration.
Data Engineering Skills:
- Expertise in data modeling techniques (e.g., star schema, snowflake schema).
- Solid understanding of access control mechanisms and SSO protocols.
- Experience in designing scalable ETL/ELT pipelines.
- Soft Skills:
- Strong problem-solving abilities in ambiguous environments.
- Excellent communication skills for collaborating across teams.
- Preferred Qualifications
- Bachelor s or Master s degree in Computer Science, Engineering, or a related field.
- Experience migrating on-premise systems to cloud-based platforms.
- Familiarity with modern CI/CD pipelines for deployment automation.