Senior Data Engineer

🕒 September 3

🇺🇸 United States – Remote

💵 $125.2k - $187.9k / year

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Lyric - Clarity in motion.

WebsiteLinkedInAll Job Openings

201 - 500 employees

🏥 Healthcare

💼 Consulting

📦 Logistics

Healthcare • Consulting • Logistics

Lyric is a leading healthcare technology company focused on payment integrity and accuracy solutions. With over 30 years of experience, Lyric aims to simplify the business of care by leveraging machine learning and predictive analytics to empower health plan payers. The company provides a range of solutions, including Lyric 42 Platform, Pre-Pay Editing, Diagnostics Module, Coordination of Benefits, Concept Libraries, and LyricIQ, which combines AI-powered payment accuracy services. Additionally, Lyric focuses on transparency and responsibility in technology development, ensuring enhanced payment accuracy, administrative efficiencies, and reduced provider abrasion. As a trusted partner in the healthcare industry, Lyric continues to deliver cutting-edge technologies at the crossroads of healthcare and fintech, supporting health plans and providers in the shift to value-based care.

📋 Description

• Design, build, and own data pipelines using Airflow, dbt, and Snowflake. • Implement the canonical data model in production within the architecture set by the Principal Data Engineer and contribute to that architecture. • Build automated validation and data quality checks into pipelines at defined stages. • Instrument pipelines for observability, including freshness, lineage, and failure alerting. • Contribute to self-service capabilities that provide governed data outputs to consuming teams. • Partner with consuming teams across invoicing, analytics, and reporting to understand requirements and translate them into reliable data. • Migrate and consolidate existing data workloads onto the unified framework without disrupting consumers. • Participate in an on-call rotation for pipeline and data quality incidents and incident reviews. • Maintain high engineering standards through version control, testing, code review, CI/CD, and current documentation. • Mentor engineers, share knowledge, and raise the technical level of colleagues.

🎯 Requirements

• Applicants must already be legally authorized to work in the U.S. • Visa sponsorship/sponsorship assumption and other immigration support are not available for this position. • Bachelor's degree in Software Engineering, Computer Science, or a related field. • 5+ years of experience in data engineering, building and owning production data pipelines. • Strong Snowflake experience, including streams and tasks, warehouse sizing and performance tuning, SQL optimization, and working knowledge of RBAC, clustering, and micro-partitions. • Production experience with dbt and Airflow, including how to structure models and DAGs so that someone else can maintain them. • Strong programming expertise in Python and deep SQL proficiency. • Solid data modeling skills, with experience designing schemas that serve more than one consumer and judgment about shared models versus consumer-specific extensions. • Experience building testing and data quality validation into pipelines rather than checking data after the fact. • Disciplined engineering practices: version control, code review, automated testing, and CI/CD. • Ability to work directly with non-engineering consumers of data, understand their needs, and communicate constraints and tradeoffs clearly. • Preferred: Experience with multi-tenant data platforms, including tenant isolation and per-customer variance within a shared model. • Preferred: Experience modeling data that changes over time, including event history, corrections and restatements, and point-in-time versus as-of reporting. • Preferred: Experience in healthcare claims, healthcare payments, or another regulated domain with PHI or PII handling and auditability requirements. • Preferred: Familiarity with Datadog or comparable observability tooling applied to data pipelines. • Preferred: Experience building internal tooling or platforms that other teams use directly.