Senior Data Engineer at Applaudo

About the Senior Data Engineer Role

Applaudo is seeking a Senior Data Engineer who excels at tackling complex production challenges, not just conceptualizing solutions. This role demands a proven ability to take full ownership of intricate data platforms, diagnose bottlenecks, efficiently refactor existing systems, and implement improvements that withstand real-world production demands. You will be energized by optimization efforts, focusing on accelerating queries, streamlining pipelines, and enhancing warehouse efficiency, with a track record of measurable impact from your contributions. Operating independently within an established architectural framework, you will collaborate with architects and fellow engineers, prioritizing outcomes such as clean data, reliable pipelines, and high-performing systems.

Note: This is a 6-month temporary opportunity, with potential for extension.

Key Competencies You Bring to Applaudo

• A Bachelor's Degree in Computer Science, Software Engineering, Information Systems, or a related field is preferred, or equivalent professional experience.
• Over 5 years of experience as a Data Engineer, demonstrating a history of independently building, optimizing, and managing production-scale data platforms.
• Proven expertise in safely refactoring live database schemas and executing production-grade data migrations.
• Hands-on experience in consolidating and deduplicating data within a Medallion Architecture (Bronze, Silver, Gold layers).
• Strong proficiency with Snowflake, including query profiling, performance tuning, warehouse sizing, clustering, and cost optimization techniques.
• Solid dbt experience, encompassing model design, incremental models, materializations, and testing.
• Experience in developing and refactoring Airflow Directed Acyclic Graphs (DAGs) and managing pipelines in a production environment.
• Advanced SQL skills with a strong record of diagnosing and resolving production performance issues.
• Working proficiency in Python for various data engineering tasks.
• Experience with Git and continuous integration/continuous delivery (CI/CD) practices in a production setting.
• Comfortable working with undocumented or evolving data pipelines and schemas, and capable of bringing structure to them.
• Excellent communication skills, enabling clear explanations of technical decisions and trade-offs.
• Upper-Intermediate to Advanced English proficiency (B2+/C1) is required for technical discussions.

Nice to Have Skills and Experiences

• Snowflake SnowPro certification.
• dbt Analytics Engineering certification.
• Familiarity with data lineage tools such as Monte Carlo, OpenLineage, or dbt Docs.
• Exposure to Business Intelligence (BI) or semantic layer tools.
• Experience with Change Data Capture (CDC) or streaming data pipelines.
• Experience supporting data platforms that power AI, Large Language Models (LLM), or conversational products.

Key Responsibilities and Accountabilities

• Refactor existing schemas and tables to eliminate duplication and enhance consistency within the Medallion Architecture.
• Optimize and reorganize Airflow pipelines to improve reliability and performance.
• Build, maintain, and continuously improve dbt models that drive downstream analytics and product features.
• Implement effective aggregation and pre-computation strategies to reduce dashboard and chat response times.
• Profile and fine-tune Snowflake query performance to ensure a responsive, production-scale platform.
• Enhance overall warehouse efficiency, scalability, and cost-effectiveness.
• Implement robust data quality testing and validation measures to proactively identify issues before they impact production.
• Troubleshoot and resolve production data issues, taking full ownership of fixes through to resolution.
• Take end-to-end ownership of your delivered solutions, from initial implementation through to ensuring production stability.