Snowflakes data engineer

Job Summary

We are looking for an experienced Data Engineer with strong hands-on expertise in Snowflake, dbt, AWS, and Sigma BI to build and maintain a modern cloud-based data platform. The candidate will be responsible for data ingestion, transformation, data quality, performance optimization, and delivering analytics-ready data for business reporting.

The role involves modernizing legacy SQL Server, SSIS, and SSAS workloads into a scalable, secure, and automated cloud data platform using Snowflake, dbt, and Fivetran.

Key Responsibilities

• Design, configure, and manage Snowflake databases, schemas, warehouses, roles, security policies, and development environments.

• Build and maintain data ingestion pipelines using Fivetran for operational, legacy, and SaaS data sources.

• Develop and optimize dbt models for data transformation, validation, reconciliation, and analytics.

• Migrate legacy SQL Server, SSIS, and SSAS ETL processes to Snowflake and dbt.

• Implement data architecture across raw, staging, curated, and reporting-ready layers.

• Configure AWS services and integrations, including S3, IAM, KMS, and secure Snowflake connectivity.

• Implement incremental loading, CDC, and Slowly Changing Dimension (SCD Type 2) processing.

• Develop automated data quality checks, freshness monitoring, and source-to-target reconciliation.

• Monitor data pipelines, troubleshoot failures, and resolve schema drift and data processing issues.

• Optimize Snowflake query performance, warehouse utilization, and overall platform costs.

• Support Sigma BI and other reporting tools by delivering trusted, well-documented datasets.

• Implement Git-based version control, CI/CD, and automated deployment workflows.

• Maintain technical documentation, data lineage, operational runbooks, and platform standards.

Required Skills

• Snowflake: Strong hands-on experience in Snowflake engineering, architecture, SQL, and performance tuning.

• dbt: Experience developing, testing, and maintaining dbt models and transformation workflows.

• AWS: Knowledge of S3, IAM, KMS, and secure cloud data integrations.

• Sigma BI: Experience supporting BI reporting, analytics, and reporting-ready data models.

• Fivetran: Experience with cloud-based data ingestion, connectors, and pipeline management. Candidates with comparable ingestion tools may also be considered if willing to learn Fivetran.

• SQL: Strong SQL development, query optimization, data validation, and reconciliation skills.

• Experience with legacy data warehouse migration, particularly SQL Server, SSIS, and SSAS.

• Knowledge of CDC, incremental loading, source-to-target mapping, and data quality frameworks.

• Understanding of data security, governance, metadata management, and data lineage.

Nice to Have

• Snowflake SnowPro Core or Advanced certification.

• Experience optimizing Snowflake costs for large-scale enterprise or financial data workloads.

• Familiarity with Snowflake Dynamic Tables and dbt-specific materializations.

• Experience with medallion architecture, including Bronze, Silver, and Gold data layers.

• Knowledge of CI/CD automation and modern data engineering best practices.

Ideal Candidate

The ideal candidate should have strong hands-on Snowflake, dbt, AWS, and Sigma BI experience, with the ability to modernize legacy ETL workloads and build reliable, scalable, and cost-efficient cloud data pipelines. Fivetran experience is preferred, but candidates with experience in similar ingestion tools who can learn Fivetran may also be considered.