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Lead Data Engineer - R01571409 at Brillio | Swiftcruit
Experience Range: 8- 10 years of experience in data engineering, with hands-on expertise in Snowflake, dbt, and AWS cloud services Key Responsibilities:
Develop, maintain, and optimize dbt models, macros, and tests to support scalable ETL/ELT data pipelines
Administer and manage Snowflake data warehouses, including databases, schemas, roles, and security configurations to ensure robust data governance
Optimize complex SQL queries and warehouse performance, reducing processing times and improving storage utilization
Manage and integrate AWS services such as S3, Lambda, Secret Manager, IAM, and CloudWatch to build and maintain reliable cloud data infrastructure
Implement and maintain CI/CD pipelines for automated deployment and release management of data solutions
Configure and monitor data quality checks, alerting systems, and performance monitoring to ensure high data reliability and integrity
Troubleshoot and resolve production issues, conducting thorough root cause analysis to minimize downtime and prevent recurrence
Collaborate closely with analytics, business intelligence, and engineering teams to deliver high-impact, scalable data solutions aligned with business objectives
Medallion modeling: Design, build, and maintain dbt models across Bronze → Silver → Gold layers for the assigned domain.
Governance alignment: Partner with the Data Governance team so models meet certification and quality-gate standards before promotion.
Downstream support: Support data modeling for downstream analytics platform consumers (dashboards and data products)
Troubleshooting & support: Diagnose and resolve pipeline issues; participate in on-call/support rotation as needed.
Documentation: Document data lineage, model logic, and key technical decisions so the work is maintainable by the internal team.
Maintain and Develop APIs
Required Skills:
Advanced proficiency in SQL (basic and advanced)
Expertise in developing and managing dbt models, macros, and tests
Hands-on experience with Snowflake data warehousing, including Time Travel and Fail Safe features
Strong understanding of ETL/ELT fundamentals and best practices
Proficiency in Python for data engineering and automation tasks
Administration of Snowflake warehouses, databases, schemas, and role-based security
Management of AWS services such as S3, Lambda, Secret Manager, IAM, and CloudWatch
Implementation and maintenance of CI/CD pipelines for data deployments
Configuration of monitoring, alerting, and data quality checks in cloud data platforms
Preferred Skills:
Experience with modern data platform fundamentals and architecture
Expertise in optimizing large-scale data pipelines for performance and cost efficiency
Familiarity with data governance and compliance best practices in cloud environments
Knowledge of infrastructure-as-code tools for cloud resource management
Exposure to advanced Snowflake features such as data sharing and secure data exchange
Desired Qualifications:
Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related field
Relevant industry certifications in AWS, Snowflake, or dbt are highly desirable