Staff Data Platform Engineer, Community Support Platform
Airbnb
Staff Data Platform Engineer, Community Support Platform
Job Description
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: Community Support Platform organization keeps our hosts and guests supported throughout the entire Airbnb experience. At its core, the CS Data Platform team provides the trusted data foundation and metrics for the most important data across offline and online consumption, empowering operations, analytics, engineering, product, and leadership teams with data they can trust. The Difference You Will Make: In order to ship data products (e.g. tables, metrics, dashboards, etc.), the team and data practitioners are transforming data generated from different sources (internal, external) with various internal frameworks and technologies with different guarantees, schema definition languages and processing modalities. We’re looking for people who thrive at the intersection of platform and data engineering: combination of strong technical skills, creativity, and a passion for engaging with and empowering data practitioners and make it easier to deliver consistent, tested, and observable data—backed by automation and guardrails (CI/CD), data contracts, and robust monitoring.
A Typical Day
- Work closely with the core data engineering team, data services team, and other product engineering teams in the Community Support Platform, understanding their productivity and data authoring pain points, and build solutions to resolve them scalably and flexibly.
- Deeply understand the different logging and data processing frameworks and collaborate with data infrastructure teams and evolve how we integrate data flows between different frameworks and serving layers worlds, ML and non-ML, and allow systems to deal with data more effectively.
- Own challenges end-to-end, proactively addressing gaps and acquiring new skills to resolve complex issues.
- Mentor and inspire your teammates in enabling code quality, operational excellence, and shared learning.
- Participate in all phases of software development from architecture/design through implementation, testing, and on-call.
- Develop, automate and standardize: logging, enriching, serving data for ML training, inference, benchmarking and monitoring (anomaly detection, safe deploys) to build the next generation of Generative AI products.
- Enable data engineers and analytics engineers to author data products.
- Design, build, and maintain robust and efficient data pipelines and APIs that collect, process, and serve data from various sources, including backend events logged as part of LLM flows, customer interactions across multiple channels, CS agents, LLM evaluations etc.
Your Expertise
- 9+ years of industry experience at the intersection of platform data engineering and software engineering with BS, MS or PhD in CS or similar.
- Proven ability to not only developing data processing pipelines, but design guardrails and abstractions that scale—reducing toil and raising confidence for all engineers.
Benefits
- bonus
- equity
- benefits
- Employee Travel Credits
How We'll Take Care of You
$204,000—$255,000 USD
Locations
- United States,
Salary
204,000 - 255,000 USD / yearly
204,000 - 255,000 USD / yearly
Source: xAI estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Deep experience building distributed batch/streaming pipelines (e.g., Spark, Flink, Kafka) and working with distributed storage (e.g., HDFS, S3).intermediate
- Expertise with ETL orchestration tools (Airflow, Luigi, AWS Glue, etc.).intermediate
- Strong knowledge of data warehousing, relational databases (PostgreSQL, MySQL), and columnar stores (Redshift, BigQuery, ClickHouse, HBase).intermediate
- Comfort driving architectural discussions across services, repositories, and environments.intermediate
- Skilled in SQL and data processing (batch and streaming), with a track record of analyzing large datasets to uncover gaps and insights.intermediate
- Excellent collaboration and communication skills; able to influence technical direction across teams.intermediate
Required Qualifications
- 9+ years of industry experience at the intersection of platform data engineering and software engineering with BS, MS or PhD in CS or similar. (experience)
- Proven ability to not only developing data processing pipelines, but design guardrails and abstractions that scale—reducing toil and raising confidence for all engineers. (experience)
Responsibilities
- Work closely with the core data engineering team, data services team, and other product engineering teams in the Community Support Platform, understanding their productivity and data authoring pain points, and build solutions to resolve them scalably and flexibly.
- Deeply understand the different logging and data processing frameworks and collaborate with data infrastructure teams and evolve how we integrate data flows between different frameworks and serving layers worlds, ML and non-ML, and allow systems to deal with data more effectively.
- Own challenges end-to-end, proactively addressing gaps and acquiring new skills to resolve complex issues.
- Mentor and inspire your teammates in enabling code quality, operational excellence, and shared learning.
- Participate in all phases of software development from architecture/design through implementation, testing, and on-call.
- Develop, automate and standardize: logging, enriching, serving data for ML training, inference, benchmarking and monitoring (anomaly detection, safe deploys) to build the next generation of Generative AI products.
- Enable data engineers and analytics engineers to author data products.
- Design, build, and maintain robust and efficient data pipelines and APIs that collect, process, and serve data from various sources, including backend events logged as part of LLM flows, customer interactions across multiple channels, CS agents, LLM evaluations etc.
Benefits
- general: bonus
- general: equity
- general: benefits
- general: Employee Travel Credits
Tags & Categories
Staff Data Platform Engineer, Community Support Platform
Airbnb
Staff Data Platform Engineer, Community Support Platform
Job Description
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: Community Support Platform organization keeps our hosts and guests supported throughout the entire Airbnb experience. At its core, the CS Data Platform team provides the trusted data foundation and metrics for the most important data across offline and online consumption, empowering operations, analytics, engineering, product, and leadership teams with data they can trust. The Difference You Will Make: In order to ship data products (e.g. tables, metrics, dashboards, etc.), the team and data practitioners are transforming data generated from different sources (internal, external) with various internal frameworks and technologies with different guarantees, schema definition languages and processing modalities. We’re looking for people who thrive at the intersection of platform and data engineering: combination of strong technical skills, creativity, and a passion for engaging with and empowering data practitioners and make it easier to deliver consistent, tested, and observable data—backed by automation and guardrails (CI/CD), data contracts, and robust monitoring.
A Typical Day
- Work closely with the core data engineering team, data services team, and other product engineering teams in the Community Support Platform, understanding their productivity and data authoring pain points, and build solutions to resolve them scalably and flexibly.
- Deeply understand the different logging and data processing frameworks and collaborate with data infrastructure teams and evolve how we integrate data flows between different frameworks and serving layers worlds, ML and non-ML, and allow systems to deal with data more effectively.
- Own challenges end-to-end, proactively addressing gaps and acquiring new skills to resolve complex issues.
- Mentor and inspire your teammates in enabling code quality, operational excellence, and shared learning.
- Participate in all phases of software development from architecture/design through implementation, testing, and on-call.
- Develop, automate and standardize: logging, enriching, serving data for ML training, inference, benchmarking and monitoring (anomaly detection, safe deploys) to build the next generation of Generative AI products.
- Enable data engineers and analytics engineers to author data products.
- Design, build, and maintain robust and efficient data pipelines and APIs that collect, process, and serve data from various sources, including backend events logged as part of LLM flows, customer interactions across multiple channels, CS agents, LLM evaluations etc.
Your Expertise
- 9+ years of industry experience at the intersection of platform data engineering and software engineering with BS, MS or PhD in CS or similar.
- Proven ability to not only developing data processing pipelines, but design guardrails and abstractions that scale—reducing toil and raising confidence for all engineers.
Benefits
- bonus
- equity
- benefits
- Employee Travel Credits
How We'll Take Care of You
$204,000—$255,000 USD
Locations
- United States,
Salary
204,000 - 255,000 USD / yearly
204,000 - 255,000 USD / yearly
Source: xAI estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Deep experience building distributed batch/streaming pipelines (e.g., Spark, Flink, Kafka) and working with distributed storage (e.g., HDFS, S3).intermediate
- Expertise with ETL orchestration tools (Airflow, Luigi, AWS Glue, etc.).intermediate
- Strong knowledge of data warehousing, relational databases (PostgreSQL, MySQL), and columnar stores (Redshift, BigQuery, ClickHouse, HBase).intermediate
- Comfort driving architectural discussions across services, repositories, and environments.intermediate
- Skilled in SQL and data processing (batch and streaming), with a track record of analyzing large datasets to uncover gaps and insights.intermediate
- Excellent collaboration and communication skills; able to influence technical direction across teams.intermediate
Required Qualifications
- 9+ years of industry experience at the intersection of platform data engineering and software engineering with BS, MS or PhD in CS or similar. (experience)
- Proven ability to not only developing data processing pipelines, but design guardrails and abstractions that scale—reducing toil and raising confidence for all engineers. (experience)
Responsibilities
- Work closely with the core data engineering team, data services team, and other product engineering teams in the Community Support Platform, understanding their productivity and data authoring pain points, and build solutions to resolve them scalably and flexibly.
- Deeply understand the different logging and data processing frameworks and collaborate with data infrastructure teams and evolve how we integrate data flows between different frameworks and serving layers worlds, ML and non-ML, and allow systems to deal with data more effectively.
- Own challenges end-to-end, proactively addressing gaps and acquiring new skills to resolve complex issues.
- Mentor and inspire your teammates in enabling code quality, operational excellence, and shared learning.
- Participate in all phases of software development from architecture/design through implementation, testing, and on-call.
- Develop, automate and standardize: logging, enriching, serving data for ML training, inference, benchmarking and monitoring (anomaly detection, safe deploys) to build the next generation of Generative AI products.
- Enable data engineers and analytics engineers to author data products.
- Design, build, and maintain robust and efficient data pipelines and APIs that collect, process, and serve data from various sources, including backend events logged as part of LLM flows, customer interactions across multiple channels, CS agents, LLM evaluations etc.
Benefits
- general: bonus
- general: equity
- general: benefits
- general: Employee Travel Credits
Tags & Categories