Senior Data Engineer

Job not on LinkedIn

🕒 September 11

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 50%

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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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 the medallion architecture • Own platform performance tuning and cost efficiency, including cluster/job sizing, Photon, partitioning, Z-ordering, Liquid Clustering, Auto Loader, and DBU cost governance • Architect and enforce data models supporting enterprise 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 catalogs, schemas, fine-grained 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 complex production data 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 retrieval-augmented generation patterns on governed Unity Catalog data • Collaborate with data science and analytics stakeholders on curated ML-ready Gold-layer datasets and feature pipelines • Stay current on the Databricks roadmap and recommend adoption of relevant capabilities • Help define guardrails and human-in-the-loop controls for AI-assisted and agentic engineering workflows • Mentor mid-level data engineers on Databricks best practices, code quality, and architecture • Partner with architects and engineering leads to translate business requirements into technical specifications • Collaborate with technical and non-technical stakeholders across product, security, and business teams • 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 the 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 • 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 • Scala, Microsoft Fabric/Power BI, and enterprise middleware such as Boomi are a plus

🏖️ Benefits

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