Analytics Engineer

Analytics Engineer Reports to: Manager, Analytics Engineering Job Overview The Analytics Engineer is a hands‑on individual contributor within Lantern’s centralized Analytics Center of Excellence (CoE), responsible for building, testing, releasing, and maintaining shared analytical data models that enable a distributed analytics community to confidently self‑serve insights. The role partners with analysts and analytics leaders across the business to identify common needs, close data gaps, and improve the reliability and consistency of analytics. Success is measured by data quality, adoption of certified models, smooth analytics releases, and reduced ambiguity in business reporting. Location: Dallas, TX – Hybrid schedule (3x in office per week) Responsibilities Data Modeling & Analytics Engineering Design and maintain fact and dimension models optimized for dashboards, reporting, and self‑service analytics in Databricks using dbt. Explore and onboard new or external data sources, developing Bronze and Silver layer models that make data usable by analysts. Implement approved “single source of truth” KPI logic in Silver and Gold models, ensuring accuracy, consistency, and maintainability. Maintain clear documentation to support adoption and correct usage by the analytics community. Apply established SDLC practices, including Git-based version control, code reviews, and participation in QA/UAT. Collaboration & Enablement Partner with Business Analysts, Finance, Operations, and Strategy teams to translate recurring analytics needs into scalable, shared models. Act as an enablement resource for a distributed analytics community by answering questions, providing guidance, and coaching on data usage and SQL best practices. Improve shared data assets based on analyst feedback and usage patterns rather than building one‑off solutions. Production Support & Deployment Implement automated data tests (schema, freshness, and business logic) as part of regular development work. Support and lead analytics releases, including regression testing, release documentation, release notifications, and post‑release validation. Perform level‑1 triage of data quality and performance issues, resolving issues where possible and escalating to Data Engineering when required. Collaborate with Data Engineering to address source data issues and identify performance optimizations. Requirements Required 3–6 years of experience in analytics engineering or closely related data roles. Strong SQL skills with experience delivering production analytical data models. Hands‑on experience with dbt (Core or Cloud). Experience with cloud data platforms such as Databricks or Snowflake. Experience working with regulated data (PII/PHI). Ability to communicate data changes and assumptions clearly to non‑technical partners. Experience working with large datasets, performing data validation, comparison, and reconciliation tasks. Strong proficiency in Microsoft Excel for data analysis, reconciliation, and reporting. Preferred Experience with medallion or layered data architectures. Exposure to automated data quality tooling (e.g., dbt tests, Soda). Familiarity with orchestration and deployment workflows (Airflow, Azure Data Factory). Experience supporting Finance, Operations, or Commercial analytics use cases. Benefits Medical Insurance Dental Insurance Vision Insurance Short & Long Term Disability Life Insurance 401(k) with company match Paid Time Off Paid Parental Leave Lantern does not discriminate on the basis of race, sex, color, religion, age, national origin, marital status, disability, veteran status, genetic information, sexual orientation, gender identity or any other reason prohibited by law in provision of employment opportunities and benefits. #J-18808-Ljbffr