Lead Data Engineer (Snowflake, DBT & Azure) (Locals Only)

Role: Data Engineer (Snowflake, DBT & Azure)

Location: Locals to Morristown, NJ (Hybrid)

Job Description:

Understand the Business End to End.

Understand the Application Architecture.

Responsible for Designing and building Applications.

Understand the project timelines and deadlines.

Provide Impact analysis for New requirements or changes.

Responsible for low level design with the team.

Convey architectural solutions to all levels of professionals and leaders.

Ensure Code Quality and Deliverables.

Lead the team and deliverables -Prioritize work with stakeholders.

Understand and follow the current Code Build and Deployment patterns across all environments.

Perform checkouts of the code deployments before the QA starts testing.

Required Qualifications

Overall, 10+ years of experience required.

Design, develop, and maintain scalable data pipelines using DBT, Snowflake, and Azure services.

Build and optimize ELT/ETL workflows for data ingestion, transformation, and integration from multiple source systems.

Develop and maintain data models, marts, and semantic layers using DBT best practices.

Implement robust data warehousing solutions in Snowflake, ensuring high performance and scalability.

Optimize Snowflake objects, queries, warehouses, clustering, and storage utilization.

Establish data quality frameworks, testing strategies, and monitoring using DBT tests and custom validation mechanisms.

Utilize Azure services such as Azure Data Factory (ADF), Azure Synapse Analytics, Azure Databricks, and Azure Storage.

Implement CI/CD pipelines and DevOps practices for data engineering deployments.

Collaborate with business stakeholders, data analysts, architects, and development teams to gather requirements and deliver data solutions.

Ensure adherence to security, governance, compliance, and data management standards.

Troubleshoot production issues and provide performance tuning recommendations.

Mentor junior engineers and contribute to data engineering best practices.

Experience working in Agile methodologies and Scrum teams.

Strong SQL development and query optimization skills.

Experience designing and implementing dimensional data models.

Knowledge of data governance and data quality frameworks.