Job Summary
This role is for a senior developer with seven to nine years of experience focused on data engineering and cloud based storage using Amazon S3 and Snowflake. The position involves building reliable data ingestion pipelines managing Snowflake tasks and streams and optimizing Snowflake SQL for analytics. The role operates in a hybrid work model during day shifts with no travel requirements supporting efficient and secure data driven outcomes.
Responsibilities
- Design and implement robust data pipelines that ingest structured and semi structured data into Amazon S3 and Snowflake environments to enable reliable analytics for business stakeholders.
- Develop and manage automated Snowflake tasks that orchestrate data loading scheduling and monitoring to ensure timely availability of curated datasets.
- Configure and maintain Snowflake streams to capture change data and support near real time data processing for critical reporting and downstream applications.
- Write optimize and refactor complex Snowflake SQL queries to improve performance resource usage and accuracy across large scale datasets.
- Build and operate Snowpipe based ingestion flows that deliver continuous data loading from Amazon S3 and other sources while maintaining data quality and integrity.
- Collaborate with data architects analysts and product teams to translate business requirements into scalable technical solutions within Snowflake and Amazon S3.
- Implement strong governance practices for data access security and compliance across Snowflake and Amazon S3 ensuring that data usage aligns with organizational standards.
- Troubleshoot and resolve production issues related to Snowflake tasks streams Snowpipe jobs and SQL logic providing timely fixes and preventive improvements.
- Document data models pipeline designs and operational procedures in clear technical artifacts to support maintainability knowledge sharing and onboarding.
- Perform capacity analysis and tuning activities within Snowflake to manage cost performance and storage while aligning with project and enterprise constraints.
- Guide peers in adopting best practices for coding testing and deployment of data solutions using Snowflake features and Amazon S3 capabilities.
- Coordinate effectively in a hybrid work model by using collaboration tools and structured communication to keep stakeholders informed about progress and risks.
- Contribute to continuous improvement by evaluating new Snowflake features and data engineering techniques that can enhance business insights and societal impact through trustworthy data.
Qualifications
- Demonstrate seven to nine years of experience in data engineering or development roles with a consistent focus on building production grade data solutions.
- Show hands on expertise with Amazon S3 including design of bucket structures lifecycle policies and integration patterns for analytics workloads.
- Exhibit deep proficiency in Snowflake SQL encompassing advanced query design optimization window functions joins and data transformation logic.
- Display practical experience configuring Snowflake tasks streams and Snowpipe to automate ingestion workflows and change data capture at scale.
- Apply solid understanding of data warehousing concepts including dimensional modeling data partitioning and performance tuning for analytical queries.
- Use strong skills in version control and collaborative development practices to support teamwork and reliable release management in hybrid environments.
- Possess clear communication and documentation capabilities that enable effective interaction with technical and non technical partners across global operations.
Certifications Required
good to have
