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Senior Data Engineer - job 1 of 2

Job Description

About the role

At Going, we’re on a mission to help people travel and experience the world. As a bootstrapped and profitable travel-tech company with over 2M subscribers, we’re evolving from a deal-alert platform to a data-powered travel experience. The Data team is integral to this transformation, supporting engineering, product, and analytics initiatives across the organization.

We’re hiring a Senior Data Engineer to lead our efforts in designing, building, and scaling a robust data infrastructure. In this role, you’ll be a key player in shaping the future of our data ecosystem, ensuring it’s scalable, efficient, and designed to support high-impact decision-making. You’ll combine technical expertise with strategic leadership, collaborating across teams to elevate our data capabilities to deliver exceptional value to our members.

This role will report to the Director of Data.

We will prioritize applications received by December 13 to ensure timely review and response. While applications may remain open after this date, those submitted later may experience a slower review process.

Key Responsibilities

  • Design and architect complex data pipelines and ETL processes using distributed computing frameworks

  • Develop and maintain data lakehouse leveraging modern data lake technologies

  • Implement and optimize data ingestion, transformation, and storage strategies across multiple cloud platforms

  • Create and maintain data engineering best practices, including performance optimization, data quality, and governance

  • Collaborate with data science and analytics teams to support advanced analytics and machine learning initiatives

  • Develop and implement data modeling techniques for large-scale datasets

  • Ensure high availability, fault tolerance, and performance of data infrastructure

  • Conduct code reviews and mentor junior data engineering team members

  • Troubleshoot and resolve complex data infrastructure and pipeline issues

What you know

Required:

  • 6+ years of professional experience in data engineering, including 2+ years in a technical leadership role.

  • Proficiency in big data technologies (e.g. Spark, Kafka, distributed computing frameworks)

  • Proficiency in cloud platforms (AWS EMR, Glue, Databricks, data lake and lakehouse solutions)

  • Expertise in Python, SQL, and modern data engineering frameworks (e.g., dbt, Airflow)

  • Experience with containerization and orchestration (Docker, Kubernetes)

  • Strong track record of delivering scalable, resilient data pipelines with demonstrated ability to architect end-to-end data solutions

  • Experience with advanced analytics workflows, including supporting machine learning models and notebook-based data science.

  • Proven ability to collaborate with cross-functional stakeholders, translating technical challenges into business solutions.

  • Familiarity with CI/CD pipelines and data governance best practices.

  • You’re legally authorized to work in the United States and able to work US-hours.

Preferred:

  • AWS cloud platform certifications

  • Databricks certifications

  • IAM and security configuration experience

  • CloudFormation or Terraform infrastructure as code

  • Experience with real-time data processing and streaming technologies (e.g., Kafka, Event Hub).

  • Knowledge of subscription-based business models and their data challenges.

  • Proficiency in implementing data privacy and security measures.

Benefits & Perks you’ll love…

  • The starting salary for this role is $165,000 + equity

  • 100% remote work environment

  • Annual team retreats, with past destinations including Washington D.C., Vancouver, Punta Cana, and Mexico City.

  • Open vacation policy, with a 15-day minimum

  • Comprehensive health, vision, dental, and life insurance

  • 401(k) with a 5% match

  • $750/quarter remote work, wellness, and wisdom stipend

  • Up to 12 weeks of paid family leave

  • Meetup stipend when you cross paths with a co-worker

  • Continuing education & development reimbursement

  • Challenging problems to solve and an awesome team to collaborate with every single day

We want you to bring your authentic self to work every single day. We accept you for who you are and consider everyone on an equal opportunity basis without regard to ancestry; age; appearance; color; gender identity and/or expression; genetics; family or parental status; marital, civil union, or domestic partnership status; mental, physical, or sensory disability; national, social or ethnic origin; past or present military service; sexual orientation; socioeconomic status; race; religion or belief. Going is an E-Verify employer.

‍If you require a reasonable accommodation or assistance for any part of the interview and employment process, please contact us at careers@going.com and let us know the nature of your request.

We want you to bring your authentic self to work every single day. We accept you for who you are and consider everyone on an equal opportunity basis without regard to ancestry; age; appearance; color; gender identity and/or expression; genetics; family or parental status; marital, civil union, or domestic partnership status; mental, physical, or sensory disability; national, social or ethnic origin; past or present military service; sexual orientation; socioeconomic status; race; religion or belief; hair length; organ donor status. Going is an E-Verify employer.

‍If you require a reasonable accommodation or assistance for any part of the interview and employment process, please contact us at careers@going.com and let us know the nature of your request.

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Average salary estimate

$165000 / YEARLY (est.)
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$165000K
$165000K

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What You Should Know About Senior Data Engineer , Going

At Going, we’re on an exciting journey to transform how people experience travel, and we need a talented Senior Data Engineer to join our dynamic team! With over 2 million subscribers, we’re shifting from a traditional deal-alert platform to a cutting-edge data-driven travel experience. As a Senior Data Engineer, you'll be at the forefront of this transformation, taking on the challenge of designing and developing robust data infrastructures that support our engineering, product, and analytics teams. Your role will be crucial in architecting and optimizing complex data pipelines and ETL processes using distributed computing frameworks. With your deep expertise in cloud platforms like AWS and technologies like Spark, you'll develop and maintain a modern data lakehouse that enhances our data capabilities. Collaboration is key, so you'll have the opportunity to work closely with our data science and analytics teams to support advanced analytics initiatives. If you love solving complex problems and mentoring junior engineers, you’ll find your place here. We value your unique perspective and skills, and we’re excited to see how you can elevate our data ecosystem. Join us at Going and help shape the future of travel experiences through data innovation!

Frequently Asked Questions (FAQs) for Senior Data Engineer Role at Going
What are the main responsibilities of a Senior Data Engineer at Going?

As a Senior Data Engineer at Going, you'll design and architect data pipelines, develop and maintain data lakehouses, and optimize data ingestion strategies. Your collaboration across teams will support advanced analytics and machine learning initiatives, driving high-impact decisions.

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What qualifications are required for the Senior Data Engineer position at Going?

To qualify for the Senior Data Engineer role at Going, you should have at least 6 years of professional experience in data engineering, with 2 years in a technical leadership role. Proficiency in big data technologies and cloud platforms like AWS is also essential.

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What technologies will I be working with as a Senior Data Engineer at Going?

In your role at Going, you'll work with modern data technologies such as Spark, Kafka, and distributed computing frameworks. Additionally, you'll be utilizing cloud platforms including AWS, as well as Python, SQL, and modern data engineering frameworks like dbt and Airflow.

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What benefits does Going offer to its Senior Data Engineers?

Going provides an attractive compensation package, starting at $165,000, remote work opportunities, an open vacation policy, comprehensive health benefits, 401(k) matching, and professional development reimbursements. Plus, annual team retreats to fantastic locations!

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How can I apply for the Senior Data Engineer position at Going?

You can apply for the Senior Data Engineer position at Going by submitting your application before the priority deadline of December 13. Make sure to include your resume and a cover letter detailing your relevant experience and why you're a great fit for the team.

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Common Interview Questions for Senior Data Engineer
Can you explain your experience with big data technologies?

When answering this question, share specific technologies you've used, such as Spark or Kafka, and how you've applied them in past projects. Highlight any challenges you've faced and how you overcame them.

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What data modeling techniques do you find most effective?

Discuss various data modeling techniques you've implemented, such as star schema or snowflake schema. Explain why you prefer certain techniques based on project needs or performance considerations.

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How have you ensured data quality in your previous roles?

Talk about specific practices you've put in place, such as validation checks or automated testing. Mention how you collaborated with data governance teams to maintain high data quality standards.

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Describe a complex data pipeline you developed.

Provide an overview of a specific data pipeline you've built, including the technologies used. Focus on the design process, challenges faced, and how you ensured its scalability and reliability.

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How do you manage collaboration with cross-functional teams?

Discuss your approach to communication and teamwork, emphasizing your ability to translate technical concepts for non-technical stakeholders and how you engage with teams to align on objectives.

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What role does cloud technology play in your data engineering projects?

Explain the importance of cloud platforms in your work, mentioning specific services like AWS EMR or Glue that you've utilized. Highlight how these technologies enhance scalability and availability.

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How do you approach performance optimization in data processing?

Describe the techniques you use for performance optimization, such as partitioning data, using efficient algorithms, and conducting load testing. Share examples of how these practices improved results.

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Can you share your experience with machine learning workflows?

Discuss your involvement in machine learning projects, including how you've prepared data for model training and collaboration with data science teams. Highlight any specific tools or frameworks you've used.

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What steps do you take to troubleshoot data pipeline issues?

Detail your troubleshooting process, which might include monitoring tools, logs analysis, and systematic troubleshooting steps. Share a specific incident where you resolved a critical issue.

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What is your approach to mentoring junior data engineers?

Talk about your mentoring style, including how you provide guidance and support to junior engineers. Share tips for fostering their growth and helping them navigate challenges in data engineering.

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G By Going

Going is on a mission to enable people to travel and experience the world. We're facilitating endless family and friend reunions, realizing bucket list destinations, and helping people make memories that will last a lifetime. We’re making travel...

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January 27, 2025

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