Lantern Data Engineer interview questions & guide 2026

Your preparation should focus on demonstrating both deep technical expertise and a "customer-first" mindset. Lantern interviewers look for engineers who understand that their "code" is a service to the broader business.

Technical Competence – You must demonstrate mastery over Python, SQL, and big data frameworks like Spark. Interviewers will look for your ability to write clean, maintainable code and your capacity to tune queries for performance in relational databases like Microsoft SQL Server.

Problem-Solving & Architecture – You will be evaluated on your ability to structure ambiguous challenges. When presented with a design problem, start by clarifying requirements, identifying constraints, and then proposing a scalable, fault-tolerant solution.

Collaboration & Communication – Because you will work with non-technical stakeholders, your ability to explain complex data concepts is critical. Focus on how your technical decisions directly support the Lantern mission of improving patient outcomes.

Cultural Alignment – Familiarize yourself with the LIGHT pillars: LOGIC, INCLUSION, GRIT, HUMANITY, and TRUTH. Be ready to provide specific examples from your past work that showcase these qualities.

The interview process at Lantern is designed to be thorough, assessing both your technical "hard skills" and your alignment with the company’s mission-driven culture. You should expect a rigorous but collaborative experience, typically beginning with a screen with the Talent Acquisition team, followed by technical deep dives and a final round focused on team fit and cross-functional collaboration.

The timeline above reflects a standard progression from initial screening to final assessment. You should interpret this as a multi-stage journey where each round builds on the last; ensure you are prepared to revisit your previous technical answers if asked to expand on them by different interviewers.

Data Pipeline Engineering

This area evaluates your ability to build, maintain, and scale data ingestion and transformation processes. Strong performance involves demonstrating a deep understanding of data movement, error handling, and performance tuning.

Be ready to go over:

• Pipeline Orchestration – How you manage dependencies and task scheduling.
• Data Quality Frameworks – Using tools like dbt tests, Great Expectations, or Soda to ensure data reliability.
• Performance Tuning – Strategies for optimizing SQL queries and Spark jobs.

Example scenarios:

• "How would you handle a schema drift in a high-volume pipeline?"
• "Describe your approach to implementing automated data quality checks."

Data Governance & Quality

Crucial for the Governance and QA role, this tests your ability to ensure that outbound data is accurate, secure, and compliant with standards like HL7 or FHIR.

Be ready to go over:

• Data Contracts – How you define and enforce standards between upstream and downstream systems.
• Automated Testing – Your experience with unit, integration, and regression testing for data products.
• Observability – How you monitor data products to catch issues before they impact the business.

Example scenarios:

• "How do you ensure data integrity for outbound client files?"
• "What is your strategy for root-cause analysis when a data quality issue is reported?"

As a Data Engineer at Lantern, your primary responsibility is to act as the bridge between raw, complex healthcare data and the actionable insights needed by our care teams. You will design and implement high-performance pipelines that ingest data from various sources, transform it into usable models, and export it securely to external partners.

You will work closely with the Data Engineering Manager and product teams to translate business requirements into technical specifications. A significant portion of your time will be spent on Data Quality—building automated frameworks that ensure our reporting is deterministic and trustworthy. You will also participate in the Technology Roadmap, conducting Proof of Concepts (PoCs) for new tools and contributing to the team's internal standards for code reviews and infrastructure management.

A strong candidate for this role will demonstrate a blend of technical expertise and a collaborative spirit.

Technical Skills

• Strong Python & SQL – These are non-negotiable for building and maintaining pipelines.
• Big Data Frameworks – Experience with Spark or Databricks is highly preferred.
• Cloud Infrastructure – Proficiency with Azure (preferred), AWS, or GCP, particularly with Infrastructure as Code (Terraform).
• Data Modeling – Solid understanding of dimensional and normalized modeling techniques.

Experience & Soft Skills

• 3-5+ years of experience in data engineering or related roles.
• Communication – The ability to translate complex technical findings into a business context is essential.
• Healthcare Domain Knowledge – Prior experience with HL7, X12 EDI, or FHIR is a significant advantage.

Q: How long does the hiring process typically take? The process usually moves at a steady pace, generally spanning 3 to 5 weeks from the initial recruiter screen to the final decision.

Q: Is the role fully remote? No, this is a hybrid role. Candidates are expected to be in the Dallas, TX office at least 3 to 4 days per week, as indicated by the specific position requirements.

Q: What is the most important trait for a candidate to demonstrate? Beyond technical skill, the ability to show GRIT—the drive to tackle big, complex problems—and HUMANITY—the ability to keep the end-user (the patient) in mind—are what separate top candidates from the rest.

Q: Should I focus more on coding or system design? For Data Engineer II and Senior roles, expect a balanced split. You must be able to code your way out of a problem, but you also need to demonstrate the architectural thinking required to build systems that last.

• Showcase your impact: When discussing past projects, always tie your work to a business outcome. Don't just say "I built a pipeline"; say "I built a pipeline that reduced data latency by 40%, allowing our care team to respond to patients 2 hours faster."
• Embrace the Pillars: Explicitly reference the LIGHT values during your interviews. It shows you have done your homework and are a culture add.
• Prepare for Ambiguity: In system design, you may not be given all the requirements. Ask clarifying questions. The interviewer wants to see how you think, not just if you know a specific tool.
• Master the Basics: Do not overlook SQL performance tuning. It is a fundamental skill that every Data Engineer at Lantern is expected to possess at an expert level.

The Data Engineer role at Lantern is an opportunity to build technology that truly matters. By ensuring the reliability, quality, and accessibility of healthcare data, you are directly contributing to the well-being of millions of members. Prepare by grounding your technical skills in practical, real-world scenarios and by internalizing the company's core values.

You have the potential to make a significant impact here. Take the time to reflect on your past projects, refine your ability to communicate complex ideas, and approach your interviews with the confidence that you are prepared for the challenge. You can find additional resources and insights to further your preparation on Dataford. Good luck—your journey to helping people get back to the lives they love starts here.

The compensation data above provides a broad range for engineering roles at Lantern. Keep in mind that your final offer will be determined by your specific level (II vs. Senior), your years of relevant experience, and the technical depth demonstrated during the interview process.