Senior Director, Head of Data Engineering

Needham Remote


Plan your next trip, read reviews and get travel advice from our community on where to stay and what to do. Find savings on hotels, book the perfect tour or attraction, and reserve a table at the best restaurants.

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Senior Director – Head of Data Engineering - Remote position with occasional visits to Needham HQ

Who we are:

We believe that we are better together, and at Tripadvisor we welcome you for who you are. Our workplace is for everyone, as is our people powered platform. At Tripadvisor, we want you to bring your unique perspective and experiences, so we
can collectively revolutionize travel and together find the good out there.

This is a leadership position that will have exposure across the entire business, influencing   the   vision   and   implementation   of   Data   Engineering   and   Enterprise systems, and other user generated content, to help consumers plan their perfect
trip, and apply the latest advances in Generative AI technologies across Tripadvisor.

A Head of Data Engineering is a senior-level position responsible for overseeing and leading the data engineering team within an organization. This role plays a crucial part in managing the data infrastructure, ensuring data quality, and facilitating data-driven decision-making. Specifics for a Head of Data Engineering may vary depending on the organization's size, industry, and specific needs, but here is a general overview of the key responsibilities and qualifications associated with this

What you’ll do

The Head of Data Engineering is responsible for managing and leading the data engineering team to design, build, and maintain data pipelines, data warehousing, and data infrastructure to support the organization's data needs. This role ensures
data quality, availability, and accessibility for various stakeholders, enabling data-driven decision-making and analytics.

Key Responsibilities:

Leadership and Team Management:

  • Lead and manage a team of Senior data engineers, data architects, and ETL (Extract, Transform, Load) specialists.
  • Provide guidance, mentorship, and professional development opportunities to team members.
  • Foster a collaborative and high-performance work culture within the data engineering team.

Data Architecture and Infrastructure:

  • Define and implement the data architecture and infrastructure strategy.
  • Oversee the design and development of data pipelines, data warehouses, and data lakes.
  • Ensure scalability, reliability, and performance of data systems.

Data Quality and Governance:

  • Establish and enforce data quality standards and data governance practices.
  • Implement data validation and cleansing processes to maintain high-quality data.
  • Ensure compliance with data privacy and security regulations.

Data Integration and ETL:

  •  Manage the development of ETL processes to extract, transform, and load data from various sources.
  • Integrate data from diverse systems and sources into a centralized 
  • Optimize data integration workflows for efficiency and accuracy.

Technology Stack Management:

  • Evaluate and select data engineering tools and technologies.
  • Keep up-to-date with industry trends and best practices.
  • Manage relationships with vendors and third-party service providers.

Data Collaboration:

  • Collaborate with data scientists, analysts, and business stakeholders to understand data requirements.
  • Ensure that data is accessible to those who need it for analysis and reporting.

Performance Monitoring and Optimization:

  • Monitor the performance of data systems and proactively address any  issues.
  • Optimize data infrastructure for speed, cost, and efficiency.
  • Budget and Resource Management:
  • Develop and manage the data engineering budget.
  • Allocate resources effectively to meet project and organizational goals. 

Skills & Experience:

  • Bachelor's or Master's degree in a relevant field (e.g., Computer Science, Information Technology, Data Science).
  • Proven experience in data engineering, including ETL, data warehousing, and data integration.
  • Strong leadership and team management skills.
  • Proficiency with data engineering tools and technologies (e.g., SQL, Hadoop, Spark, data warehouses, ETL tools).
  • Excellent problem-solving and analytical abilities.
  • Knowledge of data privacy and security regulations.
  • Strong communication and collaboration skills.
  • Familiarity with cloud computing platforms (e.g., AWS, Azure, Google Cloud) is often preferred.
  • Industry-specific certifications (e.g., AWS Certified Data Analytics, Google Cloud Professional Data Engineer) may be a plus

If you need a reasonable accommodation or support during the application or the recruiting process due to a medical condition or disability, please reach out to your individual recruiter or send an email to and let us know the nature of your request . Please include the job requisition number in your message.










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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: Architecture AWS Azure Computer Science Data Analytics Data governance Data pipelines Data quality Data Warehousing Engineering ETL GCP Google Cloud Hadoop Pipelines Privacy Security Spark SQL

Perks/benefits: Career development Travel

Region: Remote/Anywhere
Job stats:  11  3  0

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