AirflowApachePythonSQLAILarge Language ModelsClaudeAnalyticsApache AirflowGitHubVersion ControlCollaboration
About this role
Role Overview
Support the identification, investigation, and resolution of data discrepancies across marketing platform data sources including Meta, Google, TikTok, and others
Monitor data pipelines for anomalies, failures, and latency issues; escalate and help address incidents in a timely manner
Write and maintain SQL-based queries and transformation logic to support consistent marketing data across reporting layers
Assist with orchestration workflows using tools such as Apache Airflow, including helping to diagnose DAG failures and flag scheduling issues
Develop and maintain Python scripts to support data quality checks, recurring ingestion processes, and operational automation
Use GitHub for version control and collaborate with teammates on code reviews and deployment of data logic updates
Work within development environments including Visual Studio Code and Cursor to build, test, and iterate on data and automation workflows
Actively incorporate and help develop AI-assisted workflows leveraging tools like Claude to support day-to-day tasks: writing and debugging code, drafting documentation, and accelerating data investigations
Support broader AI initiatives and projects across the team as needs evolve
Maintain clear documentation of pipelines, data definitions, and troubleshooting processes to support team continuity
Partner with marketing analysts and reporting teams to understand data needs and surface issues that may impact downstream reporting
Support ad hoc data investigations and analyses as needed
Requirements
BA/BS; 1–2 years of experience in a data analyst, marketing analytics, or data operations role (internship experience considered)
Intermediate SQL proficiency — comfortable writing complex queries, joining and transforming datasets, and debugging transformation logic
Foundational knowledge of Python for data tasks, automation, or scripting
Robust attention to detail and a methodical approach to diagnosing data issues
Experience using GitHub or other version control systems for code management and collaboration
Comfort working in modern development environments such as Visual Studio Code or Cursor
Experience integrating AI tools, including large language models like Claude, into daily work for tasks like code generation, debugging, documentation, and analysis
Exposure to or curiosity about workflow orchestration concepts; awareness with tools like Apache Airflow is a plus but not required