Data Engineer II

tripadvisor; United States; Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Health benefits

Annual tuition assistance

Annual lifestyle benefit

Charitable donation matching

Employee referral scheme

Travel-related perks and discounts

Job summary

Tripadvisor is seeking a Data Engineer II for a data platform engineering team to design and sustain pipelines and production software powering analytics, experimentation, and ML workloads. The role blends data engineering with platform engineering across a broad tech stack and emphasizes end-to-end feature delivery with globally distributed engineers.

The candidate will design ETL/ELT pipelines, build reusable datasets, own pipeline lifecycles, and write production-grade Java and Python.

Qualifications

• 4–5+ years in data engineering or software engineering.
• Proficient in production Java and Python with CI/CD and code-review discipline.
• Experience designing large-scale batch or streaming data systems.
• Comfort operating cloud infrastructure, ideally AWS, with Linux and build-tool fluency.
• Ability to communicate clearly with technical and non-technical partners and take ownership independently.

Responsibilities

• Design, build, and maintain ETL/ELT data pipelines for terabytes to petabytes of data.
• Develop reusable, well-modeled datasets for analytics, data science, CRM, and ML teams.
• Own the full lifecycle of pipelines: define SLAs, monitor performance, detect anomalies.
• Write production-quality Java and Python across ingestion, event processing, REST services, and tooling.
• Build and operate streaming and batch systems powering real-time and analytical workloads.
• Collaborate with product, analytics, and data science stakeholders to translate needs into solutions.

Skills

Java

Python

CI/CD

Cloud (AWS)

Linux

Communication

Ownership

Tools

Apache Airflow

Spark

Flink

Postgres

Job description

Role overview

A data platform engineering team is hiring a Data Engineer II to design and sustain the pipelines and production software that power large-scale analytics, experimentation, and machine-learning workloads. The work blends data engineering with platform engineering, combining disciplined software craftsmanship with pipeline design at petabyte volumes. The role suits someone who enjoys building features end-to-end, working across a broad technology stack, and shipping frequently alongside globally distributed engineers.

Responsibilities

• Design, build, and maintain ETL/ELT data pipelines that move terabyte-scale data through warehouse and lakehouse platforms.
• Develop reusable, well-modeled datasets consumed by analytics, data science, CRM, machine learning, and other internal teams.
• Own the full lifecycle of pipelines: define service-level objectives, monitor performance, and detect anomalies.
• Write production-quality Java and Python across ingestion, event processing, REST services, and internal tooling.
• Build and operate streaming and batch systems that power both real-time and analytical workloads.
• Collaborate with product, analytics, and data science stakeholders to translate ambiguous needs into reliable solutions.

Requirements

• 4–5+ years of experience in data engineering or general software engineering roles.
• Strong, hands-on proficiency with production Java and Python, including CI/CD and code-review discipline.
• Experience designing large-scale batch or streaming data systems.
• Comfort operating cloud infrastructure, ideally on AWS, with Linux and build-tool fluency.
• Ability to communicate clearly with technical and non-technical partners and take ownership independently.
• Genuine curiosity and willingness to learn new tools as the stack evolves.

Nice to have

• Familiarity with stream-processing frameworks such as Flink or Spark Streaming.
• Experience with task orchestration tools like Apache Airflow or comparable systems.
• Exposure to additional technologies such as GraphQL, React, Postgres, or Gradle.
• Background designing infrastructure for large-scale data processing in Hive, Snowflake, or NoSQL databases.
• Understanding of data governance practices and tooling.
• Interest in or experience with machine learning, data science, or generative AI workloads.

Benefits and work setup

• Remote-friendly collaboration with flexible scheduling and trust-based accountability.
• Competitive compensation including base salary and an annual bonus.
• Health benefits with competitive premiums and an employee assistance program.
• Annual tuition assistance for qualifying programs and an annual lifestyle benefit.
• Charitable donation matching and a generous employee referral scheme.
• Travel-related perks and discounts.