Senior Analytics Engineer at Airbnb

Short Description:

This job is for an Analytics Engineer at Airbnb's India location, offering remote work. The role involves collaborating with cross-functional teams to enhance data quality and build essential data assets. Responsibilities include developing data models and pipelines, creating metrics and dimensions, and improving data tooling. The candidate should have at least 6 years of industry experience, proficiency in SQL, data modeling, and a programming language (e.g., Python), as well as strong attention to detail and collaborative skills. Preferred qualifications include ETL framework experience, data visualization skills, and familiarity with experimentation and machine learning techniques.  

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About the Company:

In 2007, Airbnb emerged when two hosts graciously welcomed three guests into their San Francisco residence. Since then, it has evolved into a global platform, with over 4 million hosts facilitating more than 1 billion guest arrivals in nearly every corner of the world. Each day, hosts provide unique accommodations and experiences that enable travelers to authentically connect with communities.

About the Team:

Our Analytics Engineers play a crucial role in building upon our data foundation. We are currently seeking an individual with expertise in several areas, including metric development, data modeling, SQL, Python, and working with large-scale distributed data processing frameworks such as Presto or Spark. Using these tools in conjunction with our advanced internal data resources, you will be responsible for transforming data from our data warehouse into essential data assets that fuel impactful analytical use cases, such as metrics and dashboards, and empower downstream data consumers. As an Analytics Engineer, you will work at the intersection of data science, product analytics, and data engineering, collaborating with cross-functional teams to achieve highly impactful outcomes. Your role will be instrumental in driving the transformation of how we operate through the enhancement of data quality and tooling.

Responsibilities:

1. Gain an understanding of data requirements by collaborating with fellow Analytics Engineers, Data Scientists, Data Engineers, and Business Partners.
2. Architect, develop, and launch efficient and dependable data models and pipelines in partnership with our Data Engineering team.
3. Design and implement metrics and dimensions to facilitate analysis and predictive modeling.
4. Create and develop data resources that enable self-service data consumption.
5. Construct tools for auditing, error logging, and data table validation.
6. Collaborate with Data Engineering to define logging requirements.
7. Establish and share best practices for metric, dimension, and data model development in the context of analytics.
8. Enhance data tooling in collaboration with Data Platform teams.
9. Become a technical authority on data model usage.
10. Take ownership of and review code changes related to certified metric and dimension definitions.
11. Manage communication regarding updates and changes to data models across the organization.
12. Ensure comprehensive documentation of data models, and provide clear descriptions and metadata for metrics and dimensions.

Minimum Qualifications:

1. Strong passion for maintaining high data quality and advancing data science efforts.
2. A minimum of 6 years of relevant industry experience.
3. Proficiency in SQL and optimization of distributed systems (e.g., Spark, Presto, Hive).
4. Experience in schema design and dimensional data modeling.
5. Proficiency in at least one programming language for data analysis (e.g., Python, R).
6. Proven ability to excel in both collaborative team environments and independent work.
7. Detail-oriented with a keen interest in acquiring new skills and tools.
8. Exceptional influence and relationship management skills.

Preferred Qualifications:

1. Experience with an ETL framework, such as Airflow.
2. Proficiency in Python, Scala, or Superset is preferred.
3. Effective storytelling and articulation skills, with the ability to translate analytical findings into clear, concise, and persuasive insights and recommendations for both technical and non-technical audiences.
4. An eye for design when creating dashboards and visualization tools.
5. Familiarity with experimentation and machine learning techniques.
   

Location - India (Remote)

Please click here to apply.