Senior Data Engineer

Job not on LinkedIn

🔥 0 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 25%

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Kindercare

WebsiteLinkedInAll Job Openings

1 - 1 employees

🏥 Healthcare

🧘 Wellness

Healthcare • Wellness

Kindercare is a medical practice focused on identifying and addressing factors that contribute to health conditions linked to allergies, nutritional status, and environmental influences. It aims to amend such conditions where possible using avoidance strategies, nutritional supplementation, lifestyle changes, and other therapeutic modalities.

📋 Description

• Design, build, and optimize production-grade ETL/ELT pipelines across Bronze, Silver, and Gold medallion layers • Own Databricks platform performance tuning and cost efficiency, including cluster/job sizing, Photon, partitioning, Z-ordering, Liquid Clustering, Auto Loader, and DBU governance • Architect and enforce data models supporting Microsoft Fabric/Power BI and downstream analytics products • Build and maintain CI/CD pipelines for Databricks assets using Asset Bundles, Repos, and Git-based deployment • Integrate platform pipelines with middleware, source systems, and cloud-native services • Administer and evolve Unity Catalog, including access control, lineage, row/column-level security, and workspace-catalog bindings • Implement data quality, observability, reliability, monitoring, alerting, and SLA management practices • Partner with security, compliance, and audit teams to maintain SOX ITGC alignment • Troubleshoot production pipeline issues, perform root-cause analysis, and implement preventive fixes • Create architecture documentation, procedures, and operational runbooks • Evaluate, pilot, and productionize Databricks-native AI/ML capabilities including Genie, MLflow, Feature Store, and Model Serving • Support vector search and RAG patterns on governed Unity Catalog data • Prepare curated ML-ready Gold-layer datasets and feature pipelines with data science and analytics stakeholders • Track the Databricks roadmap and recommend Lakehouse AI, Mosaic AI, and agent framework adoption • Define guardrails and human-in-the-loop controls for AI-assisted and agentic engineering workflows • Mentor mid-level data engineers on Databricks practices, code quality, and architecture • Translate business requirements into technical specifications for BI and AI products • Collaborate with product, security, business, data science, and analytics stakeholders • Contribute to data governance, security, and privacy standards

🎯 Requirements

• Bachelor’s degree in computer science, information systems, engineering, statistics, or related field or equivalent work experience • 7+ years of experience as a data engineer • 3+ years specifically architecting and operating production workloads on Databricks • Strong understanding of data governance, data security, and access control best practices • Experience with Agile development methodologies, CI/CD automation, and Test-Driven Development • Excellent problem-solving skills and ability to lead technical troubleshooting independently • Strong written and verbal communication skills with ability to explain technical concepts to non-technical stakeholders • Demonstrated experience owning a lakehouse/medallion architecture at scale, including data modeling for BI consumption • Experience operating in a governed or regulated environment (SOX, HIPAA, or similar) with formal change control and access governance • Deep, hands-on expertise with Databricks Lakehouse Platform: Delta Lake, Unity Catalog, Delta Live Tables / Lakeflow, Workflows, and cluster/job optimization (Photon, Auto Loader, Liquid Clustering) • Advanced SQL and strong Python (PySpark) development skills; comfort with Scala a plus • Experience with Databricks Asset Bundles, Repos, and CI/CD for lakehouse deployments • Working knowledge of cloud data services (Azure preferred — ADLS, Azure SQL, Synapse/Fabric; AWS/GCP equivalents acceptable) and cloud migration patterns • Hands-on experience with MLflow for experiment tracking, model registry, and lifecycle management • Working knowledge of Databricks AI/ML capabilities — Feature Store, Model Serving, Genie, Mosaic AI, or equivalent lakehouse ML tooling • Exposure to vector search, embeddings, or RAG architectures • Comfort partnering with data science teams on ML-ready data pipelines • Databricks certifications strongly preferred • Familiarity with Microsoft Fabric/Power BI and enterprise middleware such as Boomi a plus

🏖️ Benefits

• Discounted child care benefits • Medical, dental, and vision benefits for employees’ families and pets • Employee assistance programs supporting mental health and personal growth • Health and wellness programs • Paid time off • Discounts for work necessities, such as cell phones