Senior Data Engineer

Reporting to the Director of Data Engineering, the Senior Data Engineer will design, build, and maintain reliable, scalable data pipelines and models that power our business. In this role, you’ll own data solutions end-to-end, partnering with teams across PerkSpot to turn business and source-system requirements into dependable, production-ready solutions. You’ll bring strong data engineering fundamentals and hands-on experience with modern technologies like SQL, dbt, cloud data warehouses, Python, and workflow orchestration tools.

What you’ll accomplish:

• Design and build scalable batch and event-driven data pipelines from ingestion through consumption.
• Develop and maintain reliable data models using SQL and dbt.
• Build and optimize solutions on Snowflake or a comparable cloud data warehouse.
• Create and manage orchestrated workflows using Airflow, Dagster, or similar tools, including dependencies, schedules, retries, failure handling, and backfills.
• Integrate data from databases, APIs, files, cloud storage, and third-party platforms using Python to automate workflows and support pipeline development.
• Implement testing, monitoring, alerting, logging, and data-quality controls to improve pipeline reliability.
• Troubleshoot pipeline failures, performance issues, and data discrepancies while optimizing for performance, scalability, and cost.
• Apply software engineering practices including Git, code reviews, CI/CD, documentation, and automated testing.
• Partner with analytics, product, engineering, and business teams to translate requirements into dependable data solutions.
• Mentor other engineers and contribute to data architecture and engineering standards.

What we’re looking for:

• 5+ years of experience in data engineering or a related role.
• Advanced SQL skills, including complex transformations, query optimization, and dimensional data modeling.
• Hands-on experience with dbt, including models, tests, macros, documentation, and incremental processing.
• Experience with Snowflake or a similar cloud data warehouse.
• Experience building solutions in AWS or Azure.
• Proficiency in Python for data processing, automation, and integration.
• Hands-on experience with Airflow, Dagster, or another workflow orchestration platform.
• Demonstrated experience building and supporting data pipelines end to end.
• Strong understanding of workflow dependencies, scheduling, retries, backfills, and failure recovery.
• Strong understanding of ETL/ELT patterns, data warehousing, and data-quality practices.
• Experience using Git and CI/CD within a collaborative development environment.
• Strong troubleshooting, communication, and documentation skills.

Preferred qualifications include:

• Experience with Azure Data Factory, Snowpipe, Snowflake Streams and Tasks, or comparable technologies.
• Experience working with APIs, JSON, event-driven pipelines, and cloud object storage.
• Familiarity with medallion architecture and dimensional modeling.
• Experience implementing pipeline observability, lineage, and automated alerting.
• Experience modernizing legacy stored-procedure or scheduler-based pipelines.
• Familiarity with data governance, security, and role-based access controls.