Data Platform Engineer II - ETL Pipelines - Remote

Doist; Oxford; Hybrid; GBP 65,000 - 90,000; Full time

Job summary

Tripadvisor Group is hiring a Data Engineer II to design, build, and sustain scalable data infrastructure powering its travel platform. You will develop production-grade ETL/ELT pipelines, data models, and governance across Snowflake, BigQuery, and Hive while writing Java and Python and collaborating with global teams.

You’ll work on streaming and batch systems (Flink/Spark/Kafka), maintain cloud infrastructure on AWS, and contribute to analytics, data science, and ML initiatives in a fast-paced

Qualifications

• 4–5+ years of data engineering or software development experience in a commercial setting.

Responsibilities

• Design, build, and maintain robust ETL/ELT data pipelines across Snowflake, BigQuery, Hive, and other platforms.
• Develop scalable data models and curated data sets for analytics, data science, CRM, ML, and other data consumers.
• Own full lifecycle of data pipelines: define SLAs, monitor performance, and ensure data integrity and governance.
• Write production Java and Python code; build streaming and batch processing systems (Flink, Spark, Kafka).
• Operate AWS cloud infrastructure and improve CI/CD processes; collaborate with Product, Analytics, and Data Science teams.

Skills

Java

Python

ETL/ELT pipelines

SQL

Data modeling

Analytical skills

REST services

AWS

CI/CD

Linux

Education

Bachelor's degree in Computer Science or Engineering

Tools

Hadoop

Hive

BigQuery

Snowflake

Kafka

Spark

Flink

Airflow

Gradle

AWS

Job description

Tripadvisor Group is hiring a Data Engineer II to design, build, and sustain scalable data infrastructure powering its travel platform. You will develop production-grade ETL/ELT pipelines, data models, and governance across Snowflake, BigQuery, and Hive while writing Java and Python and collaborating with global teams.

You’ll work on streaming and batch systems (Flink/Spark/Kafka), maintain cloud infrastructure on AWS, and contribute to analytics, data science, and ML initiatives in a fast-paced