Senior Snowflake Data Engineer to design, build, and optimize scalable data solutions within complex enterprise environments. This is a hands-on engineering role focused on developing reliable data pipelines, improving Snowflake performance and cost efficiency, and modernizing existing data-processing workloads.

You will collaborate with data architects, analysts, DevOps engineers, and client stakeholders to deliver secure, maintainable, and high-performing data platforms. The ideal candidate combines strong Snowflake expertise with advanced SQL and Python skills and has experience delivering data solutions in cloud-based enterprise environments.

Key Responsibilities :

- Design, develop, and maintain scalable data pipelines and transformation workflows within Snowflake.

- Build and optimize ELT/ETL processes using SQL, Python, Snowpark, dbt, and Snowflake-native capabilities.

- Modernize existing Python- and stored-procedure-based pipelines using set-based processing, incremental loading, and reusable engineering patterns.

- Implement Snowflake-native data-processing solutions using Dynamic Tables, Streams, Tasks, and stored procedures.

- Improve platform performance and cost efficiency through query tuning, warehouse right-sizing, clustering strategies, workload isolation, and auto-suspend and auto-resume policies.

- Develop reliable orchestration, dependency management, monitoring, error handling, retry, and recovery mechanisms.

- Design and maintain dimensional, relational, and domain-oriented data models.

- Implement data-quality checks, observability, testing, lineage, and documentation standards.

- Integrate data from batch and real-time sources using tools such as Fivetran, Kafka, Airflow, or similar technologies.

- Contribute to CI/CD pipelines, infrastructure-as-code practices, and automated deployment processes.

- Work closely with architects and client stakeholders to translate business and technical requirements into production-ready solutions.

- Participate in code reviews, technical design discussions, estimation, and Agile delivery activities.

Required Qualifications :

- 7+ years of experience in data engineering, including significant hands-on experience with Snowflake.

- Advanced SQL skills, including complex transformations, query optimization, and stored procedure development.

- Strong Python development experience for data processing, automation, and pipeline development.

- Hands-on experience with Snowpark and Snowflake-native capabilities such as Dynamic Tables, Streams, and Tasks.

- Proven experience designing and supporting scalable ELT/ETL pipelines in production environments.

- Strong understanding of Snowflake performance and cost optimization, including warehouse sizing, query profiling, clustering, and workload management.

- Experience with data modeling, incremental processing, pipeline orchestration, and dependency management.

- Experience with dbt or a comparable data transformation framework.

- Familiarity with at least one major cloud platform: AWS, Azure, or GCP.

- Experience with Git, CI/CD, automated testing, and modern software delivery practices.

- Strong troubleshooting, analytical, and problem-solving skills.

- Effective written and verbal communication skills, including the ability to collaborate directly with technical and business stakeholders.

Preferred Qualifications :

- Experience with Fivetran, Kafka, Airflow, or similar ingestion and orchestration tools.

- Familiarity with Terraform or another infrastructure-as-code platform.

- Experience with Snowflake Iceberg Tables or modern lakehouse architectures.

- Exposure to Snowflake Cortex, including Cortex Analyst, Cortex Search, or Cortex LLM functions.

- Experience supporting business continuity and disaster recovery strategies.

- SnowPro Core or SnowPro Advanced certification.