Snowflake Data Engineer

Data Engineer – Modern Data Platform

Role Overview

We are looking for an experienced, hands-on Data Engineer with strong expertise in Fivetran, dbt, Snowflake , and modern cloud data engineering practices. The candidate should also have experience with Python , and familiarity with AI-assisted development tools such as Claude, Cursor, or VS Code-based AI assistants .

The role will focus on building scalable ingestion and transformation pipelines, implementing data quality and orchestration patterns, and supporting enterprise data products consumed by analytics and business teams.

Core Responsibilities

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 , including 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.

Required Technical Skills

Strong hands-on experience with:

Snowflake – Advanced SQL, data modeling, performance optimization, RBAC, stages, and data integration patterns.

dbt / dbt Cloud – Models, tests, macros, incremental models, sources, documentation, jobs, and deployment patterns.

Fivetran – Connector configuration, schema management, sync troubleshooting, monitoring, and ingestion architecture.

SQL – Complex joins, CTEs, window functions, reconciliation, and query optimization.

Git / CI/CD – Branching, pull requests, code reviews, and automated deployment workflows.

Python

Working knowledge of Python is preferred, particularly for data processing, automation, API integrations, file processing, data validation, and operational scripting.

Advanced Python development is not required, but candidates should be comfortable reading, troubleshooting, and developing Python-based data engineering utilities.

AI-Assisted Development

Familiarity with Claude and AI-assisted development workflows is preferred; deep AI/LLM development experience is not required .

Candidates should be comfortable using tools such as:

Claude

Cursor

VS Code with AI-assisted development capabilities

Typical use cases may include:

Developing and troubleshooting SQL, dbt, and Python code.

Code review, refactoring, and debugging.

Generating unit/data-quality tests.

Understanding existing codebases and data pipelines.

Creating technical documentation.

Accelerating day-to-day data engineering development while following enterprise security and development standards.

Good to Have

Apache Airflow / AWS MWAA for orchestration.

AWS services such as S3, IAM, Lambda, Secrets Manager, and FSx .

Salesforce, Marketo, and other SaaS integrations.

REST API and SFTP/file-based ingestion.

Snowflake Secure Data Sharing.

Snowpark / Snowpark Container Services (SPCS).

Databricks.

Terraform / Infrastructure as Code.

Data quality and observability frameworks.

Experience modernizing or migrating legacy ETL/integration platforms.

Preferred Experience

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.

Candidate Profile

We are specifically looking for a hands-on Data Engineer , rather than primarily a BI/reporting developer.

The ideal candidate should be comfortable owning and troubleshooting the complete data lifecycle:

Source → Fivetran → Snowflake → dbt

The candidate should also be comfortable using Claude through modern development environments such as Cursor or VS Code to improve engineering productivity, troubleshooting, documentation, and code quality.

Manage data modelling projects. Ensure adherence to policies. Provide strategic guidance. Lead a team.

Graduate in Computer Science, Data Science, or a related field. 4-6 years of experience in data modelling or data analysis.