Tech Lead - Snowflake & DBT
About the role
Mitra Innovation is seeking a highly experienced, hands-on Lead or Principal Data Engineer to support enterprise data modernization initiatives for a US-based client. The role focuses on designing, developing, optimizing, and maintaining scalable data transformation pipelines using Snowflake and DBT, as well as modernizing existing data processing systems. The position is primarily hands-on engineering (about 80% development) with additional responsibilities for technical guidance, code reviews, architectural decisions, and mentoring other engineers. Candidates should be able to independently own complex deliverables, provide technical leadership, and deliver high-quality results with minimal supervision. The company is a trusted technology partner to over 50 global clients, specializing in digital transformation.
Must have
- At least 5+ years of substantial hands-on Snowflake experience in production data engineering environments.
- Strong understanding of Snowflake architecture, SQL processing, warehouse management, and performance optimization.
- Experience developing, troubleshooting, and maintaining complex transformation pipelines on Snowflake.
- Ability to independently diagnose performance, data quality, and processing issues.
- At least 5+ years of hands-on dbt experience, preferably involving large-scale, production-grade projects.
- Strong practical experience with dbt Core and/or dbt Cloud.
- Advanced proficiency in dbt models, materialisations, incremental processing, testing, dependencies, and project configuration.
- dbt Analytics Engineering Certification or dbt Architect Certification.
- Strong experience developing reusable dbt macros, Jinja-based transformations, and modular dbt architectures.
- Understanding of dbt development, deployment, testing, and documentation best practices.
- Experience maintaining and improving complex dbt projects involving multiple data sources and interdependent models.
- Expert-level SQL skills, including complex joins, CTEs, window functions, conditional logic, aggregations, and advanced data transformations.
- Strong SQL debugging, query optimization, and data discrepancy investigation capabilities.
- Experience designing and implementing dimensional, relational, and analytical data models.
- Deep understanding of ETL/ELT architectures, enterprise data warehousing, and modern data engineering design patterns.
- Experience working with large datasets and complex data transformation requirements.
- Proven ability to investigate data mismatches, identify root causes, and implement reliable corrections.
- Strong experience with Git/GitHub-based development, version control, branching strategies, and code reviews.
- Experience working in structured development and release environments.
- Ability to independently interpret requirements, design solutions, and deliver production-quality implementations.
- Strong analytical reasoning, debugging, and problem-solving skills.
- 12+ years of overall experience in data engineering, data warehousing, ETL/ELT, or related software engineering roles preferred.
- Proven experience delivering complex data engineering projects using Snowflake and dbt.
- Previous experience as a Senior, Lead, Staff, or Principal Data Engineer, or equivalent hands-on technical leadership experience.
- Demonstrated ability to take ownership of complex deliverables with minimal day-to-day supervision.
- Experience guiding other engineers and contributing to technical design and implementation decisions.
- Strong written and verbal communication skills, particularly when collaborating with distributed and offshore teams.
Nice to have
- Experience migrating legacy data pipelines from Microsoft SQL Server, PostgreSQL, SSIS, or other ETL platforms into Snowflake and dbt.
- Experience with Python for data processing, automation, testing, and engineering utilities.
- Familiarity with AWS services, particularly S3 and cloud-based data ingestion architectures.
- Experience with dbt Fusion and modern dbt development environments.
- Knowledge of CI/CD automation for dbt and Snowflake.
- Experience with AI coding assistants or agents such as Claude Code, GitHub Copilot, or similar tools.
- Familiarity with KNIME and other enterprise ETL tools.
- Experience working with CRM, marketing, fundraising, direct mail, or multi-client data platforms.
- Experience with reusable data models, metadata-driven transformations, and configurable client-specific processing.
- Familiarity with JIRA and Agile delivery methodologies.
Technologies
- Agile
- Ai
- Analytics
- Automation
- AWS
- CI/CD
- Claude Code
- Cloud
- CRM
- Data Engineering
- Data Ingestion
- Data Modeling
- Data Pipelines
- Data Warehousing
- dbt
- ELT
- ETL
- Git
- GitHub
- GitHub Copilot
- Jira
- PostgreSQL
- Python
- S3
- Snowflake
- SQL
- SQL Server
- SSIS
- Test Automation
Highlights
The role is for a project with a client based in the USA. Candidates should have 12+ years of overall experience in data engineering or related fields. dbt Analytics Engineering Certification or dbt Architect Certification is required. Experience in a distributed, fast-paced engineering environment is expected.
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