Lead Data Engineer - R01571409

Lead Data Engineer

Job requirements 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