Priceline
online travel
DataEngineer
Neural analysis suggests this role is
optimal for Mid candidates.
“Data Engineer at Priceline. Skills: Data Pipeline Development, Data Ingestion, Data Transformation, Data Validation, Data Architecture, Data Modeling, SQL, Spark, Airflow, Snowflake, dbt, Big Data, Apache Spark, Kafka, GCP, CloudSQL, MySQL, PostgreSQL, BigQuery, Oracle, Java, Python. building and maintaining reliable, scalable, and high-performing data pipelines. designing, developing, and optimizing data ingestion, transformation, and validation processes”
What You'll Achieve.
deliver trusted data for analytics and product initiatives; ensure data solutions meet business and product requirements; ensure reliable outputs; support analytics, reporting, and product features; ensure transparency of data availability, integrity, and lineage for stakeholders; Support release readiness by validating that data pipelines deliver accurate and timely data
Industry & Context.
analyze, debug, and resolve data processing issues efficiently
What They're Looking For.
Must Have
3–5 years of hands-on experience building and maintaining data pipelines and architectures in a corporate or product-driven environment., Proficient with SQL and modern data tools (e. g. , Spark, Airflow, Snowflake, dbt), Demonstrated expertise in Big Data solutions, including frameworks such as Apache Spark and Kafka., command of databases, including CloudSQL (MySQL, PostgreSQL), BigQuery, and Oracle., Proficiency in data orchestration frameworks, particularly Apache Airflow, for scheduling and managing complex workflows., Proven ability to analyze, debug, and resolve data processing issues efficiently., Proficient in Java or Python, with the ability to write efficient, maintainable code in either language., Illustrated history of living the values necessary to Priceline: Customer, Innovation, Team, Accountability and Trust, Unquestionable integrity and ethics are essential.
Nice to Have
Proficiency in the Google Cloud Platform (GCP) stack is highly desirable., Familiar with data governance, security protocols, and compliance best practices
What You'll Do.
building and maintaining reliable
and high-performing data pipelines
and optimizing data ingestion
and validation processes
Build and optimize data pipelines for ingestion
Assist with CI/CD practices to automate pipeline deployment and monitoring
Develop and maintain data validation and quality assurance tests to ensure reliable outputs
Build and maintain data models that support analytics
Define solution parameters for data preparation
Monitor and report on data pipeline performance
and data quality issues
Ensure transparency of data availability
and lineage for stakeholders
Support release readiness by validating that data pipelines deliver accurate and timely data
How You'll Work.
Team & Collaboration
collaborating closely with Data Architects, Product Managers, and other stakeholders; Work in tandem with Data Architects to align on data architecture requirements; Partner with Product Managers, Analysts, and Engineering teams to understand data requirements; Facilitate communication between data, product, and development teams to ensure alignment; Provide guidance on best practices for data management and pipeline design
Communication Scope
Facilitate communication between data, product, and development teams
Full Job Description
**This role is eligible for our hybrid work model: Two days in-office.** Our Technology team is the backbone of our company: constantly creating, testing, learning, and iterating to better meet the needs of our customers. If you thrive in a fast-paced, ideas-led environment, you’re in the right place. **Why this job is a big deal:** As a Data Engineer in the Product Operating Model (POM), your focus is on building and maintaining reliable, scalable, and high-performing data pipelines that deliver trusted data for analytics and product initiatives. You are accountable for designing, developing, and optimizing data ingestion, transformation, and validation processes, while collaborating closely with Data Architects, Product Managers, and other stakeholders to ensure data solutions meet business and product requirements **In this role, you will get to: Data Pipeline Development & Optimization** * Build and optimize data pipelines for ingestion, transformation, and validation * Assist with CI/CD practices to automate pipeline deployment and monitoring * Develop and maintain data validation and quality assurance tests to ensure reliable outputs **Data Architecture & Modeling** * Work in tandem with Data Architects to align on data architecture requirements * Build and maintain data models that support analytics, reporting, and product features * Define solution parameters for data preparation, integration, and storage **Collaboration & Cross-Functional Alignment** * Partner with Product Managers, Analysts, and Engineering teams to understand data requirements * Facilitate communication between data, product, and development teams to ensure alignment * Provide guidance on best practices for data management and pipeline design **Continuous Improvement** * Identify opportunities to improve pipeline performance, reliability, and maintainability * Evaluate and implement new data tools, technologies, and frameworks * Share knowledge and mentor team members on data engineering p
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