Senior Data Engineer

Overview

We are seeking a skilled Senior Data Engineer to support our data platform initiatives. The ideal candidate will have strong experience with Snowflake and in cloud-based data engineering (AWS), hands-on SQL and Python development Key Responsibilities:

• Design, develop and maintain scalable data pipelines and ETL processes in the cloud.
• Work with stakeholders to understand data requirements and deliver solutions.
• Develop & optimize SQL queries for data extraction, transformation, and reporting.
• Build and maintain scripts and automation using Python.
• Integrate with and perform basic operations within Snowflake data warehouse.
• Ensure data quality, performance, and reliability of systems.
• Collaborate with functional teams including Data Scientists, Analysts & DevOps.
• Design and implement scalable database structures and ensure data integrity across systems.
• Analyze large and complex datasets, troubleshoot issues and support data-driven decision-making.
• Participate in data architecture discussions and contribute to best practices in database design and data governance.
• Monitor and optimize data pipeline performance, troubleshoot bottlenecks, and recommend tuning improvements.
• Participate in structured peer code reviews and deployment processes to ensure production readiness and reduce risk.
• Take part in initiatives to continuously improve version control practices and deployment workflows.
• Participate in root cause analysis sessions to identify the impact of data issues and improve long-term system stability.

Required Skills

& Experience:

• Strong SQL development skills and solid understanding of database design principles, indexing strategies, and normalization.
• Expert-land optimization in SQL (e.g., T-SQL, PL/SQL) and query optimization techniques.
• Strong experience with AWS cloud services (e.g., S3, Lambda, Glue, Redshift).
• Proficiency in Python for data engineering and automation tasks.
• Experience with Snowflake or similar modern cloud-based data platforms.
• Familiarity with modern data architecture patterns and ETL best practices.
• Experience with Git and CI/CD tools for version control and deployment automation.
• Experience with orchestration tools such as Kubernetes and Airflow.
• 8+ years of hands-on experience as a Data Engineer or in a similar data-focused role.
• Experience with large, complex datasets and enterprise-scale data environments.
• Experience participating in or managing data deployment processes, with understanding of production release and risk mitigation practices.
• Detail-oriented mindset with a focus on quality, performance, and stability.
• Ability to understand the broader system and business impact of technical solutions.
• Strong analytical, problem-solving, and communication skills.

Nice to Have

• Knowledge of the US healthcare system, including claims data or HIPAA compliance.
• Experience with other cloud-based databases (e.g., AWS RDS, Azure SQL, Google Cloud SQL).
• Familiarity with scripting languages (e.g., Bash) for automation.
• Experience in Agile environments and cross-functional, remote collaboration.
• Familiarity with documentation and collaboration tools (e.g., Confluence, Jira).