Data Specialist

Brillio

. Develop, maintain, and optimize dbt models, macros, and tests for scalable ETL/ELT data pipelines .

Posted 11/12/2026full-timeBangalore • IndiaSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates advanced proficiency in SQL and expertise in developing and managing dbt models, macros, and tests for scalable ETL/ELT data pipelines. Skilled in administering Snowflake data warehouses and managing AWS services, with a strong focus on data governance and compliance best practices.

Highest-signal resume keywords

Advanced SQL ProficiencyDbt Model DevelopmentSnowflake AdministrationAWS Services ManagementCI/CD Pipeline Implementation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLDbt ModelsETL/ELT FundamentalsPythonData Pipeline OptimizationData Quality ChecksMonitoring and AlertingAPIs DevelopmentRoot Cause AnalysisInfrastructure-as-Code

Soft Skills

CollaborationProblem-SolvingDocumentation

Tools & Technologies

SnowflakeAWS S3AWS LambdaAWS Secret ManagerAWS IAMAWS CloudWatch

Certifications & Qualifications

AWS CertificationSnowflake CertificationDbt Certification

Industry Keywords

Data EngineeringData GovernanceCloud Data PlatformsData WarehousingData Quality Standards

Tech Stack

Tools & technologies

AWSCloudETLPythonSnowflakeSQL

About the role

Key responsibilities & impact

Develop, maintain, and optimize dbt models, macros, and tests for scalable ETL/ELT data pipelines
Administer and manage Snowflake data warehouses, databases, schemas, roles, and security configurations
Optimize complex SQL queries and warehouse performance
Manage and integrate AWS services including S3, Lambda, Secret Manager, IAM, and CloudWatch
Implement and maintain CI/CD pipelines for automated deployment and release management
Configure and monitor data quality checks, alerting systems, and performance monitoring
Troubleshoot production issues and conduct root cause analysis
Collaborate with analytics, business intelligence, and engineering teams
Design and maintain dbt models across Bronze, Silver, and Gold medallion layers
Partner with Data Governance to meet certification and quality-gate standards
Support downstream analytics platforms, dashboards, and data products
Participate in on-call/support rotation as needed
Document data lineage, model logic, and technical decisions
Maintain and develop APIs

Requirements

What you’ll need

8–10 years of experience in data engineering
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
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
Relevant industry certifications in AWS, Snowflake, or dbt are highly desirable