Data Engineer
Airbnb India Private LimitedJob Description
Senior Data Engineer, Payments
Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way.
The Community You Will Join:
The Payments team at Airbnb is crucial to the company's operations, handling critical data related to compliance with Tax, Payments, and Legal regulations. We also manage application data for tools such as CRM, Jira, and Workday, which are essential for Airbnb’s business. Joining this team means working with cross-functional stakeholders, designing scalable solutions, and contributing to a world-class data engineering environment with an emphasis on quality, scalability, and robust engineering practices.
The Difference You Will Make:
Our team charter is on enabling Airbnb to comply with Tax, Payments,and Legal regulations so that our Hosts can continue to operate in regulated geos. Our products ingest, process, validate, and deliver large datasets to government authorities (often partnered with tax remittance) so our data must be of the highest accuracy and quality. As you build and maintain key components of the critical Compliance data ecosystem, you’ll have the opportunity to contribute to creating standards and best practices for Airbnb’s DataEngineering. Your work on solving complex business challenges at scale will be instrumental in shaping the tools, processes, and standards used by the broader data community.
A Typical Day:
- Design, build, and maintain robust and efficient data pipelines that collect, process, and store data from various sources, including user interactions, listing details, and external data feeds.
- Develop data models that enable the efficient analysis and manipulation of data for merchandising optimization. Ensure data quality, consistency, and accuracy.
- Develop high quality data assets for product use-cases by partnering with Product, AI/ML and Data Science.
- Build scalable data pipelines (SparkSQL & Scala) leveraging Airflow scheduler/executor framework
- Collaborate with cross-functional teams, including Data Scientists, Product Managers, and Software Engineers, to define data requirements, and deliver data solutions that drive merchandising and sales improvements.
- Contribute to the broader Data Engineering community at Airbnb to influence tooling and standards to improve culture and productivity
- Improve code and data quality by leveraging and contributing to internal tools to automatically detect and mitigate issues
Your Expertise:
- 6+ years of relevant industry experience
- BE/B.tech in computer science or relevant technical degree
- Hands on experience in DSA coding -Data structure and algorithm
- Extensive experience designing, building, and operating robust distributed data platforms (e.g., Spark, Kafka, Flink, HBase) and handling data at the petabyte scale.
- Strong knowledge of Scala, or Python, and expertise with data processing technologies and query authoring (SQL).
- Demonstrated ability to analyze large data sets to identify gaps and inconsistencies, provide data insights, and advance effective product solutions
- Expertise with ETL schedulers such as Apache Airflow, Luigi, Oozie, AWS Glue or similar frameworks
- Solid understanding of data warehousing concepts and hands-on experience with relational databases (e.g., PostgreSQL, MySQL) and columnar databases (e.g., Redshift, BigQuery, HBase, ClickHouse)
- Excellent written and verbal communication skills
Our Commitment To Inclusion & Belonging:
Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.
Experience Level
Senior LevelJob role
Job requirements
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