As a Data Engineer at UKG, your day-to-day activities will revolve around building, maintaining, and optimizing the data systems that drive our business intelligence and product analytics.

• Designing and Building Pipelines: You will write clean, testable code to extract data from various transactional databases, APIs, and log files, transforming it into structured formats optimized for downstream consumption.
• Ensuring Data Quality and Reliability: You will implement automated monitoring, testing, and validation frameworks to ensure that the data flowing through our pipelines is accurate, complete, and delivered on time.
• Collaborating with Cross-Functional Teams: You will partner with product managers, data analysts, and software engineers to understand data requirements, design appropriate schemas, and deliver data products that enable informed decision-making.
• Optimizing Data Infrastructure: You will continuously monitor pipeline and query performance, refactoring legacy code and tuning database configurations to minimize processing costs and reduce latency.
• Supporting Database Reliability: You will collaborate with reliability teams to ensure high availability, disaster recovery, and data security compliance across all data storage systems.

To be competitive for the Data Engineer position at UKG, you should possess a strong foundation in software engineering and data management.

• Must-have skills:

  • Strong proficiency in SQL, including writing complex queries, window functions, and query optimization.
  • Hands-on experience building robust ETL/ELT pipelines using Python, Java, or Scala.
  • Experience with relational databases (e.g., PostgreSQL, SQL Server) and data warehousing technologies.
  • Solid understanding of data modeling concepts (dimensional modeling, star/snowflake schemas).
  • Familiarity with cloud platforms (GCP, AWS, or Azure) and containerization tools like Docker.

• Nice-to-have skills:

  • Experience with pipeline orchestration tools such as Apache Airflow.
  • Exposure to big data technologies (e.g., Spark, Hadoop) and stream processing frameworks (e.g., Kafka).
  • Background in database reliability engineering, including backup/restore strategies and high-availability setups.

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Q: How difficult is the Data Engineer interview at UKG? A: The interview difficulty is generally rated as average but highly thorough. The technical rounds are pragmatic, focusing on core SQL, practical ETL problems, and real-world system design rather than obscure algorithmic puzzles.

Q: What is the typical timeline from the initial screen to an offer? A: The entire process typically takes about 2 to 3 weeks. The talent acquisition team is highly supportive and keeps candidates updated on their progress throughout the stages.

Q: How should I prepare for the SQL portion of the interview? A: Practice both theoretical concepts (indexing, execution plans, joins) and practical query writing. Be comfortable using window functions, CTEs, and handling complex aggregations on mock datasets.

Q: Does UKG support hybrid or remote working arrangements for this role? A: UKG offers flexible working models, including hybrid and remote options, depending on the specific team, location, and role requirements. You should discuss your preferences with the recruiter during the initial screening call.

Q: What distinguishes candidates who receive offers from those who do not? A: Successful candidates demonstrate strong technical fundamentals, communicate their architectural decisions clearly, and show a genuine interest in understanding the team's specific challenges and dynamics.

• Review Your Projects Thoroughly: Be prepared to talk in detail about every project on your resume. Know the architecture, the technology choices, the data volumes, and the specific challenges you faced.
• Assess the Team Dynamics: During your interviews, take the opportunity to ask detailed questions about the team's culture, working style, and current technical challenges. Candidates are highly encouraged to review the team structure and alignment during the process to ensure a great mutual fit.
• Practice Whiteboard Design: Be ready to sketch out data pipeline architectures and explain how data flows from source systems to end-user dashboards, highlighting where validation, queuing, and storage occur.
• Focus on Clean Code: Whether writing SQL or Python during live coding, focus on readability, consistent naming conventions, and handling edge cases (such as null values or empty datasets).

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Preparing for a Data Engineer interview at UKG is an opportunity to showcase your technical expertise, problem-solving capabilities, and commitment to data quality. By focusing your preparation on advanced SQL, robust ETL design, and the architecture of your past projects, you can walk into your interviews with confidence.

Remember that UKG values engineers who are not only technically skilled but also collaborative, communicative, and aligned with a supportive team culture. Take the time to understand the team's specific goals, ask insightful questions, and demonstrate how your skills can help drive UKG's data initiatives forward.

For additional resources, detailed company insights, and community-sourced interview preparation materials, explore the tools and guides available on Dataford to help you take the next step in your career.

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The salary range reflects UKG's commitment to attracting top-tier engineering talent. When evaluating compensation, consider the entire package, including competitive base pay, comprehensive benefits, and opportunities for professional growth within a globally recognized leader in HCM technology. Use this data to align your expectations and confidently navigate your compensation discussions.