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 Secure 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

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Disclaimer: This job posting and location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Lead Data Engineer (Bengaluru)
🏢 Brillio
📍 Bengaluru