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Career Opportunities: Lead Data Engineer, Remote (354339)

This a Full Remote job, the offer is available from: United StatesLogistics at full potential.At GXO, we’re constantly looking for talented individuals at all levels who can deliver the caliber of service our company requires. You know that a positive work environment creates happy employees, which boosts productivity and dedication. On our team, you’ll have the support to excel at work and the resources to build a career you can be proud of.As the Lead Data Engineer, you will lead the design and development of robust and scalable data pipelines on a modern data platform. You will work closely with cross-functional teams to understand data requirements, implement efficient solutions, and ensure the reliability and performance of our data infrastructure. The ideal candidate will have a strong background in data engineering, expertise in working with cloud platforms such as Google Cloud Platform (GCP), and experience with modern data warehousing solutions like Snowflake. The Lead Data Engineer will mentor less experienced developers and collaborate with cross-functional teams, stakeholders, and vendors to achieve project milestones and deliver a robust and scalable data lake solution.Pay, benefits and more.We are eager to attract the best, so we offer competitive compensation and a generous benefits package, including full health insurance (medical, dental and vision), 401(k), life insurance, disability and more.What you’ll do on a typical day:• Data Pipeline Design and Development: Lead the design, implementation, and maintenance of data pipelines to support data ingestion, transformation, and storage on GCP and Snowflake.• Collaboration: Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver data solutions that meet business objectives.• Platform Optimization: Optimize and enhance the performance, scalability, and reliability of existing data pipelines, ensuring efficient data processing and storage.• Technology Stack: Stay abreast of industry trends and emerging technologies in data engineering and incorporate them into the data architecture where applicable. Experience with the following modern data stack highly preferred: GCP, Snowflake, Fivetran, and dbt.• Quality Assurance: Implement best practices for data quality, validation, and testing to ensure the accuracy and integrity of data throughout the pipeline.• Documentation: Create and maintain comprehensive documentation for data pipelines, ensuring knowledge transfer and supportability.What you need to succeed at GXO:At a minimum, you’ll need:• Bachelor’s degree in Computer Science, Data Science,or equivalent related work• 5+ in designing and building data pipelines on cloud platforms, preferably GCP and Snowflake.• Expertise in working with modern data warehousing solutions such as Snowflake, ie, Snowpipe Streaming, Warehouse Optimization, and clustering. Highly preferred, real-time data processing experience using Kafka.• Python and Advanced SQL: Must be adept at scripting in Python, particularly for data manipulation and integration tasks, and have a solid grasp of advanced SQL techniques for querying, transformation, and performance optimization.• Data Modeling: Understanding of best practices for data modeling, including star schemas, snowflake schemas, and data normalization techniques. A good understanding of the data structures that support email targeting.• ETL/ELT Processes: Experience in designing, building, and optimizing ETL/ELT pipelines to process large datasets using dbt.• Apache Airflow: Experience in building, deploying, and optimizing DAGs in Airflow or a similar tool.• GitHub: Experience with version control, branching, and collaboration on GitHub.• Data Visualization: Knowledge of tools like Superset, Looker or Python visualization libraries (Matplotlib, Seaborn, Plotly…etc)• Collaboration and Communication: Ability to work closely with data scientists, analysts, and other stakeholders to translate business requirements into technical solutions. Strong documentation skills for pipeline design and data flow diagrams.• Data Privacy: Knowledge of data privacy laws including an understanding of GDPR, CCPA, and other regulations to ensure compliance in data privacy practices.It’d be great if you also have:• Master’s degree• Snowflake Certification (highly preferred)• GCP Certification (highly preferred)We engineer faster, smarter, leaner supply chains.GXO is a leading provider of cutting-edge supply chain solutions to the most successful companies in the world. We help our customers manage their goods most efficiently using our technology and services. Our greatest strength is our global team – energetic, innovative people of all experience levels and talents who make GXO a great place to work.We are proud to be an Equal Opportunity/Affirmative Action employer. Qualified applicants will receive consideration for employment without regard to race, sex, disability, veteran or other protected status.GXO adheres to CDC, OSHA and state and local requirements regarding COVID safety. All employees and visitors are expected to comply with GXO policies which are in place to safeguard our employees and customers.All applicants who receive a conditional offer of employment may be required to take and pass a pre-employment drug test.The above statements are intended to describe the general nature and level of work being performed by people assigned to this classification. They are not intended to be construed as an exhaustive list of all responsibilities, duties and skills required of personnel so classified. All employees may be required to perform duties outside of their normal responsibilities from time to time, as needed. Review GXO's candidate privacy statement here.This offer from "GXO Logistics" has been enriched by Jobgether.com and got a 72% flex score.

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What You Should Know About Career Opportunities: Lead Data Engineer, Remote (354339), GXO Logistics

Are you ready to take your data engineering career to the next level? At GXO Logistics, we’re on the hunt for a talented Lead Data Engineer to join our dynamic team in a full remote position. As the lead for designing and developing robust data pipelines, you’ll play a pivotal role in our modern data platform transformation. Collaborating with cross-functional teams, you’ll understand their data needs while implementing efficient solutions that ensure the reliability of our data infrastructure. Your expertise in cloud platforms, particularly Google Cloud Platform (GCP), and modern data warehousing solutions like Snowflake will be key to your success here. In this role, you'll also have the opportunity to mentor less experienced developers, helping to shape the future of our tech team. With a healthy focus on optimizing existing data pipelines, you’ll enhance performance, scalability, and reliability. Don’t worry; you'll always be up-to-date with industry trends and emerging technologies. Plus, GXO Logistics takes pride in fostering a collaborative environment, so you’ll be working closely with other data experts to drive business objectives. We offer generous benefits, including competitive pay, full health insurance, a 401(k), and much more to ensure you're happy while excelling in your role. If you have a background with advanced SQL, Python, experience in ETL processes, and a passion for data quality, we want to hear from you! Join GXO and help optimize and innovate our supply chain data solutions today!

Frequently Asked Questions (FAQs) for Career Opportunities: Lead Data Engineer, Remote (354339) Role at GXO Logistics
What responsibilities does a Lead Data Engineer have at GXO Logistics?

As a Lead Data Engineer at GXO Logistics, your primary responsibilities include designing and developing robust data pipelines, collaborating with cross-functional teams to assess their data needs, and ensuring the reliability of our data infrastructure. You will lead the optimization of existing pipelines, incorporate new technologies, and ensure that best practices for data quality are consistently implemented.

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What qualifications are needed for the Lead Data Engineer position at GXO Logistics?

To succeed as a Lead Data Engineer at GXO Logistics, candidates should have a Bachelor's degree in Computer Science, Data Science, or equivalent and at least 5 years of experience designing and building data pipelines, particularly on cloud platforms such as GCP and Snowflake. Proficiency in Python and advanced SQL techniques is essential, as well as familiarity with ETL/ELT processes and tools like Apache Airflow.

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What tools and technologies does the Lead Data Engineer at GXO Logistics work with?

The Lead Data Engineer at GXO Logistics primarily works with Google Cloud Platform (GCP) and Snowflake for data warehousing. Familiarity with tools like dbt for data transformation, Fivetran for data integration, and experience with Apache Airflow for orchestrating data pipelines are highly preferred.

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Is the Lead Data Engineer role at GXO Logistics fully remote?

Yes, the Lead Data Engineer position at GXO Logistics is fully remote, allowing you the flexibility to work from anywhere within the United States. This setup encourages a balanced work-life dynamic while being part of a supportive and innovative team.

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What benefits does GXO Logistics offer for the Lead Data Engineer position?

GXO Logistics offers a competitive compensation package alongside a comprehensive benefits package that includes full health insurance (medical, dental, vision), a 401(k) plan, life insurance, and disability coverage. We believe in investing in our employees' well-being to ensure that they can thrive in their roles.

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Common Interview Questions for Career Opportunities: Lead Data Engineer, Remote (354339)
Can you describe your experience with data pipeline design as a Lead Data Engineer?

In your answer, focus on specific projects where you designed and implemented data pipelines. Highlight your approach to scalability and performance optimization, mentioning any relevant technologies you used, such as GCP, Snowflake, and others.

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What strategies do you use for collaboration with cross-functional teams?

Discuss your communication style and how you ensure all stakeholders are aligned on data requirements. Provide examples of how you’ve previously worked with data scientists and analysts to deliver effective data solutions.

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How do you ensure data quality and reliability in your pipelines?

Explain the best practices you implement for data validation and testing within pipelines. Mention any specific tools or methodologies you use to adhere to these quality standards.

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What are your preferred tools for ETL/ELT processes?

Identify the tools you are most comfortable with, such as dbt or Apache Airflow, along with brief descriptions of how you've used them to optimize data workflows and enhance efficiency.

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How do you stay updated on emerging trends in data engineering?

Share your methods for continuous learning, whether through attending industry conferences, online courses, or by engaging with community forums and literature. Mention any specific technologies you're particularly excited about.

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Describe your experience mentoring junior data engineers.

Discuss the aspects of mentorship you find most rewarding, recounting specific examples where you've guided new team members in developing their skills, helping them overcome challenges, and fostering a collaborative learning environment.

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Can you share an example of a particularly challenging data project you led?

Focus on a specific project where challenges arose, including what the challenge was, how you approached resolving it, and the results you achieved through your leadership and technical skills.

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What is your approach to data modeling?

Discuss your understanding of data modeling best practices, including your experience with star and snowflake schemas, and how this knowledge has helped you in previous projects.

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How would you handle a situation where your team is under pressure to deliver results quickly?

Highlight your ability to prioritize tasks and implement strategies that maintain quality while meeting deadlines. Discuss any techniques you use to manage your team’s workload during high-pressure periods.

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What data privacy regulations should a Lead Data Engineer be aware of?

Mention key data privacy laws such as GDPR and CCPA. Explain why it's crucial for data engineers to be knowledgeable about these regulations, particularly in ensuring compliance during data handling and processing.

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Full-time, remote
DATE POSTED
December 9, 2024

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