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Senior Data Engineer

About PrePass

PrePass® is North America's most trusted weigh station bypass and toll management platform. We’re transforming how the transportation industry operates—creating solutions that keep trucks moving safely, efficiently, and compliantly. This means making bold decisions and building systems that support not only fleets but the broader economy. It all starts with enabling commercial vehicles to keep rolling with seamless toll management, weigh station bypass, and safety solutions. It’s what we do best, and we do it to meet the demands of the road every day.

That’s why people join us: our solutions are implemented in real-time, on highways and interstates across the nation, helping fleets go farther, faster. This work challenges and rewards, presenting complex problems that need ambitious answers. We hire bold thinkers with a heart for impact, a passion for progress, and the optimism to shape the future of transportation.

Position Description

As a Senior Data Engineer, you will be responsible for designing and developing pipelines for data ingestion, processing, and distribution. Our solutions range from batch processing to real-time data streaming. You will be challenged with identifying innovative solutions to meet the needs of our growing business. The ideal candidate has a deep understanding of data engineering, particularly in building scalable and efficient data infrastructures on cloud environments. We are looking for someone who enjoys working in a fast-paced environment, who can take on complex challenges, and produce impactful solutions.

Key Responsibilities

  • Develop and manage production ETL pipelines on the Azure cloud.
  • Formulate complex SQL queries for transforming and collating data across multiple sources.
  • Code data transformations and processing logic in Databricks.
  • Troubleshoot data integration and data quality issues, diagnose failures, implement optimal solutions, and revise procedures.
  • Tune and optimize cluster performance for cost, efficiency, scalability, and resource utilization.
  • Partner with team to design and implement a strategy for re-architecting legacy SQL Server Integration Services [SSIS].
  • Develop comprehensive solutions for traceability and observability.
  • Contribute to documentation and maintain architecture diagrams.
  • Participate in proof-of-concept exercises and prototyping. Provide analysis and recommendations based on your findings.
  • Mentor and guide junior engineers, encourage a culture of learning.

Required

  • Bachelor’s degree in computer science or equivalent experience.
  • Typically, 6+ years of industry experience in data engineering.
  • At least 3 years of experience providing technical leadership on large projects.
  • Experience using Databricks for data engineering tasks.
  • Expert in writing, analyzing, and tuning complex SQL queries.
  • Advanced experience with design and data modeling.
  • Programming proficiency in Python.
  • Familiarity with big data technologies and frameworks such as Apache Spark and Delta Lake.
  • Committed to delivering on value-added innovation. Eager to learn and experiment with new technology.

Preferred

  • Experience with stream-processing systems like Apache Spark and Kafka.
  • Familiarity of event driven architecture – queues, batches, and pub/sub models.
  • Proficiency with reporting and data visualization tools, specifically PowerBI.
  • Familiarity with data quality and governance principles and best practices.
  • Versed in software engineering practices, version control, code reviews, unit testing, and CI/CD.

How We Will Take Care of You

  • Robust benefit package that includes medical, dental, and vision that start on date of hire.
  • Paid Time Off, to include vacation, sick, holidays, and floating holidays.
  • 401(k) plan with employer match.
  • Company-funded “lifestyle account” upon date of hire for you to apply toward your physical and mental well-being (i.e., ski passes, retreats, gym memberships).
  • Tuition Reimbursement Program.
  • Voluntary benefits, to include but not limited to Legal and Pet Discounts.
  • Employee Assistance Program (available at no cost to you).
  • Company-sponsored and funded “Culture Team” that focuses on the Physical, Mental, and Professional well-being of employees.
  • Community Give-Back initiatives.
  • Culture that focuses on employee development initiatives.

Average salary estimate

$110000 / YEARLY (est.)
min
max
$90000K
$130000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Senior Data Engineer, PrePass, LLC

At PrePass, we're revolutionizing the transportation industry, and we're on the lookout for an enthusiastic and talented Senior Data Engineer to join our team. In this pivotal role, you'll be diving deep into the world of data engineering, crafting pipelines for data ingestion, processing, and distribution. Imagine working with cutting-edge technology, like Azure and Databricks, to transform how fleets operate on highways across North America. It's not just about numbers; it's about making real-time decisions that keep trucks moving efficiently and safely. You'll tackle complex challenges, optimizing ETL pipelines and SQL queries to enhance our services. Plus, your expertise will lead the charge in re-architecting our legacy systems and driving innovation. At PrePass, we value bold thinkers who are eager to make a difference and inspire others. With a robust benefits package and a supportive culture focused on growth and community, you’ll find that making an impact here is both rewarding and fulfilling. If you're passionate about building scalable, efficient data infrastructures and mentoring the next generation of engineers, we want you on our team!

Frequently Asked Questions (FAQs) for Senior Data Engineer Role at PrePass, LLC
What are the key responsibilities of a Senior Data Engineer at PrePass?

As a Senior Data Engineer at PrePass, your main responsibilities include developing and managing production ETL pipelines on Azure, complex SQL query formulation, coding data transformations in Databricks, troubleshooting data integration issues, and optimizing cluster performance. You'll also focus on re-architecting legacy systems, ensuring traceability in data processes, and mentoring junior engineers.

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What qualifications do I need to become a Senior Data Engineer at PrePass?

To qualify for the Senior Data Engineer position at PrePass, you typically need a Bachelor’s degree in computer science or a relevant field and about 6 years of industry experience, with at least 3 years in a leadership role on large projects. Proficiency in SQL, Databricks, Python, and familiarity with big data technologies like Apache Spark is also important.

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What technologies does a Senior Data Engineer work with at PrePass?

At PrePass, Senior Data Engineers primarily work with Azure for data pipelines, Databricks for data processing, and tools like SQL for data analysis. Experience with big data frameworks like Apache Spark and project management methodologies is also advantageous.

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How does PrePass support professional development for Senior Data Engineers?

PrePass offers various professional development opportunities for Senior Data Engineers, including a robust benefit package, tuition reimbursement programs, and an engaging culture that prioritizes learning. You’ll also have the chance to mentor junior engineers, fostering growth within the team.

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What is the company culture like at PrePass for Senior Data Engineers?

PrePass boasts a vibrant and inclusive company culture focused on employee development, well-being, and community involvement. As a Senior Data Engineer, you'll be part of a team that values creativity and innovation, encouraging you to make a significant impact while collaborating with passionate colleagues.

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Common Interview Questions for Senior Data Engineer
How do you approach designing ETL pipelines as a Senior Data Engineer?

Begin by understanding the data sources, the transformations needed, and the target data infrastructure. Highlight your experience with Azure ETL processes and specific tools like Databricks, detailing any previous projects where you successfully designed and implemented complex ETL systems.

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Can you describe your experience with cloud technologies in data engineering?

Discuss your hands-on experience with Azure, emphasizing any projects where you leveraged cloud capabilities to enhance data processing. Mention challenges faced, how you optimized performance, and the overall impact of the cloud solutions you implemented.

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What strategies do you use to troubleshoot data quality issues?

Outline a structured troubleshooting process, starting with identifying anomalies in the data. Discuss tools and methods you've used, such as logging or data validation checks, and provide examples of how you have resolved specific data quality issues in the past.

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How do you ensure the scalability of data pipelines?

Emphasize your approach to designing scalable architectures, such as utilizing cloud features that support horizontal scaling and employing efficient data partitioning techniques. Include examples of systems you've optimized to handle increased data loads while maintaining performance.

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What experience do you have with SQL and how do you ensure queries are optimized?

Share your extensive experience in writing and tuning SQL queries, discussing specific techniques you use to improve performance, like indexing and query refactoring. Give examples from previous roles where your query optimizations led to measurable enhancements.

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How do you mentor junior engineers as a Senior Data Engineer?

Talk about your mentorship philosophy, highlighting how you share knowledge through pair programming, code reviews, and training sessions. Mention any success stories where your guidance helped junior engineers excel in their roles.

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Describe a successful project where you used Databricks.

Detail a specific project where Databricks played a critical role, including the project objectives, the challenges encountered, and how overall data processing improved after implementing Databricks solutions. Quantify the success with metrics if possible.

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In your opinion, what are the best practices for data governance?

Discuss key principles of data governance, like data lineage, quality assurance processes, and compliance with regulations. Share personal experiences where you implemented best practices to enhance data governance and ensure high-quality data management.

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What do you find most challenging about working with big data technologies?

Be honest about the challenges, such as data volume, velocity, and variety. Discuss how you've navigated those challenges in past roles, perhaps detailing a specific instance where you implemented successful strategies to overcome them.

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How do you stay updated with the latest technologies in data engineering?

Mention your engagement with continuous learning, such as attending industry conferences, participating in workshops, or following relevant online communities. Highlight particular resources or publications you find beneficial for staying current in the field.

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PrePass Safety Alliance is the non-profit provider of PrePass weigh station bypass and toll payment services. The Alliance was formed in 1993 by trucking industry leaders, enforcement agencies and state DOTs to improve the safety and efficiency of...

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Full-time, on-site
DATE POSTED
December 4, 2024

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