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EXL

Snowflake Data Engineer

EXL

. Design, build, and support end-to-end data pipelines using Fivetran, dbt, and Snowflake .

Posted 11/5/2026full-timeNew York City • New York • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and managing end-to-end data pipelines using Fivetran, dbt, and Snowflake, with a strong focus on data modeling, SQL optimization, and production troubleshooting. Proven ability to lead data modeling projects and collaborate across teams to ensure data quality and operational efficiency.

Highest-signal resume keywords
Snowflake SQL OptimizationDbt Model DevelopmentFivetran Connector ConfigurationGit/CI/CD ExperienceData Quality Implementation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
SnowflakeSQLDbtFivetranPythonData ModelingData IntegrationRoot-Cause AnalysisData Quality FrameworksApache Airflow
Soft Skills
CollaborationTroubleshootingStrategic GuidanceLeadership
Tools & Technologies
ClaudeCursorVS CodeTerraformAWS ServicesREST APISFTPDatabricks
Industry Keywords
Data EngineeringData AnalysisData Lifecycle ManagementEnterprise SDLCChange Management

Tech Stack

Tools & technologies
AirflowApacheAWSCloudETLPythonSDLCSnowflakeSQLTerraform

About the role

Key responsibilities & impact
  • Design, build, and support end-to-end data pipelines using Fivetran, dbt, and Snowflake
  • Configure and manage Fivetran connectors across SaaS applications, databases, APIs, and file-based sources
  • Develop and maintain dbt models across staging, intermediate, mart, and publish layers
  • Implement dbt testing, source freshness, incremental processing, documentation, and reusable macros
  • Develop optimized Snowflake SQL and scalable analytical data models
  • Support Snowflake objects, security/RBAC, stages, data sharing, and data-loading patterns
  • Implement data quality, reconciliation, monitoring, and operational alerting
  • Troubleshoot production pipelines and perform root-cause analysis across ingestion and transformation layers
  • Participate in Git-based development, CI/CD, code reviews, and DEV/QA/PROD deployments
  • Collaborate with application, infrastructure, security, analytics, and business teams to onboard new data sources
  • Manage data modelling projects, ensure adherence to policies, provide strategic guidance, and lead a team
  • Own and troubleshoot the complete data lifecycle: Source → Fivetran → Snowflake → dbt
  • Use Claude through Cursor or VS Code to improve engineering productivity, troubleshooting, documentation, and code quality

Requirements

What you’ll need
  • Strong hands-on experience with Snowflake, including advanced SQL, data modeling, performance optimization, RBAC, stages, and data integration patterns
  • Strong hands-on experience with dbt/dbt Cloud, including models, tests, macros, incremental models, sources, documentation, jobs, and deployment patterns
  • Strong hands-on experience with Fivetran, including connector configuration, schema management, sync troubleshooting, monitoring, and ingestion architecture
  • Strong SQL skills, including complex joins, CTEs, window functions, reconciliation, and query optimization
  • Git/CI/CD experience with branching, pull requests, code reviews, and automated deployment workflows
  • Working knowledge of Python; advanced Python development is not required
  • Comfort reading, troubleshooting, and developing Python-based data engineering utilities
  • Familiarity with Claude and AI-assisted development workflows is preferred
  • Graduate in Computer Science, Data Science, or a related field
  • 4–6 years of experience in data modelling or data analysis
  • 5+ years of Data Engineering or related experience
  • 2+ years of hands-on experience with Snowflake and dbt
  • Production experience implementing and supporting Fivetran pipelines
  • Experience operating within enterprise DEV → QA → PROD SDLC and change-management processes
  • Experience designing reusable ingestion and transformation patterns
  • Strong production troubleshooting and root-cause analysis skills
  • Apache Airflow/AWS MWAA, AWS services, SaaS integrations, REST API, SFTP/file-based ingestion, Snowflake Secure Data Sharing, Snowpark/SPCS, Databricks, Terraform/IaC, data quality frameworks, and legacy ETL modernization are good to have