Senior Data Engineer, People Analytics

This is a fully remote position, open to applicants in United States.

📋 Description

• Collaborate with team members and stakeholders to comprehend data- and people-related business challenges and convert them into scalable data solutions.

• Develop data pipelines and tables sourced from HR systems such as Workday, Greenhouse, and additional data sources.

• Assist Data Science team members in utilizing data for reporting, dashboard creation, and other client-facing applications.

• Construct, update, and maintain a production-grade data foundation supporting AI initiatives — including pipelines for LLM-powered tools, evaluation and feedback datasets, alongside the access controls and data models necessary for responsibly scaling AI products from prototype to production.

• Design and deliver data products, such as dashboards and reporting tools (e.g., Streamlit visualization apps), that provide actionable insights for non-technical stakeholders.

• Write and optimize queries for both distributed query engines (Trino/Presto) and private relational databases (Postgres).

• Align priorities and work from a roadmap, ensuring focus on the highest-priority projects.

• Evaluate data readiness for AI applications, collaborating with EX teams, Legal, and BizTech to ensure sensitive employee data is managed with appropriate governance, permissions, and access controls.

• Facilitate the transition of AI prototypes to production by constructing the necessary infrastructure — automated pipelines, security controls, and stable data models — that prototypes need to scale.

• Demonstrate adaptability and sound judgment to support organizational agility.

• Be a continuous learner, active listener, and educator to enhance data engineering, people analytics, and Airbnb.

⛳️ Requirements

• Over 5 years of industry experience as a Data Engineer or in a closely related field.

• Highly skilled in SQL across both OLAP and OLTP environments, including Trino/Presto/Hive and Postgres syntax.

• Strong proficiency in the Ubuntu environment, demonstrating the ability to navigate, manage, and edit files on AWS instances via SSH.

• Experience with relational databases and the capability to assume an administrative role in database management.

• Proficient in Python, with a proven ability to interact with data sources (web APIs, SFTP, S3 buckets, Airtable) and efficiently process intermediate data.

• Experience with scalable data pipelines utilizing Airflow or similar scheduling/orchestration frameworks.

• Expertise in accurately implementing essential database concepts, including primary keys, indexes, nullable fields, data types, and partitioning; experience in designing data models for optimal storage and retrieval.

• Previous experience handling sensitive data, including sensitivity classification, access controls, and audit logging; familiarity with data governance requirements for employee or sensitive data.

• Experienced in building data products, dashboards, or reporting tools using lightweight frontend frameworks such as Streamlit, with visualizations that effectively communicate insights to business stakeholders.

• Proven ability to analyze large datasets to identify gaps and inconsistencies, provide data insights, interpret complex queries, and communicate findings effectively to non-technical audiences.

• Experience in creating data layers that support LLM-based tools or agentic AI frameworks, including data quality and latency requirements for model consumption, AI evaluation practices, and management of feedback loops and evaluation datasets.

• Strong comfort working collaboratively with both technical and non-technical stakeholders.

• Solid understanding of data structures and algorithms, with the ability to apply data structures to solve medium-complexity problems.

• Knowledge and proficiency in utilizing Git repositories for effective codebase management, version control, and the capability to mentor and assist peers.

• Familiarity with system design principles, particularly as they relate to data platforms or AI-integrated systems.

🏝️ Benefits

• Bonuses

• Equity

• Employee Travel Credits