Key Facts

Remote From:

Full time

Mid-level (2-5 years)

English

Hard Skills

Apache Spark SQL (Programming Language) Data Modeling Databricks Databricks Kubernetes Observability Data Lineage High Availability Design Role-Based Access Control (RBAC) +27 more

Other Skills

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Decision Making
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Communication
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Leadership
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Teamwork
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Mentorship

Roles & Responsibilities

6+ years experience building and optimizing highly scalable distributed data systems (e.g., Databricks, Spark, or Snowflake).
3+ years of experience working with SQL and data modeling on large multi-table data sets.
3+ years of experience acting as a trusted technical decision-maker in a team setting, solving for short-term and long-term business value.
3+ years of experience coaching other engineers.

Requirements:

Architect and manage scalable, high-performance distributed data environments powering healthcare analytics (Databricks Lakehouse and Snowflake), ensuring health, optimization, and security.
Develop and implement scalable and performant data solutions.
Partner with Engineering Managers, Product Managers, and stakeholders across Aledade to develop and execute technical roadmaps using Agile processes.
Mentor and coach more junior engineers, including thorough pull request reviews and receptiveness to critical feedback.

Aledade, Inc.

Health Care

About Aledade, Inc.

Aledade is the largest network of independent primary care, enabling clinicians to deliver better patient outcomes and generate more savings revenue through value-based care. Aledade’s data, personal coaching, user-friendly workflows, health care policy expertise, strong payer relationships and integrated care solutions enable primary care organizations to succeed financially by keeping people healthy. Together with more than 1,900 practices and community health centers in 45 states and the District of Columbia, Aledade manages accountable care organizations that share in the risk and reward across more than 200 value-based contracts representing more than 2.5 million patient lives. To learn more, visit www.aledade.com.

Company type: Scaleup

Industry: Health Care

Founded: 2018

Company size: 1001 - 5000

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Job description

As a Senior Data Platform Engineer II, you will architect and manage the high-performance, distributed data environments that power our healthcare analytics. You will move beyond traditional maintenance to ensure our Databricks Lakehouse and Snowflake environments scale indefinitely. You will be responsible for the health, optimization, and security of our data platforms, making complex data accessible and expressive for web applications and AI.

Primary Duties:

Develop and implement scalable and performant solutions.

Partner, as a peer, with Engineering Managers, Product Managers, and stakeholders throughout Aledade to develop and execute technical roadmaps using Agile processes.

Mentor and coach more junior engineers including thorough pull request reviews for other developers and be receptive to critical feedback on your own work.

Minimum Qualifications:

BS/BTech (or higher) in Computer Science, Engineering or a related field or equivalent experience.

6+ years experience as an engineer building and optimizing highly scalable distributed data systems (e.g., Databricks, Spark, or Snowflake).

3+ years of experience working with SQL and data modeling on large multi-table data sets.

3+ years of experience acting as a trusted technical decision-maker in a team setting, solving for short-term and long-term business value.

3+ years of experience coaching other engineers.

Preferred KSA’s:

Platform & Infrastructure (The "Databricks/Cloud" Core)

Databricks & Lakehouse Architecture: Deep expertise in managing Databricks workspaces, including Unity Catalog for data governance, lineage, and fine-grained access control.

Infrastructure as Code (IaC): Advanced proficiency with Terraform (or similar) to automate the provisioning and scaling of Databricks clusters, cloud resources (AWS preferred), and networking.

Snowflake Proficiency (Nice-to-Have): Experience managing Snowflake environments, specifically focusing on warehouse cost optimization, security integration, and secure data sharing.

Modern Database Internals: In-depth knowledge of distributed systems, including partitioning, liquid clustering/Z-Ordering, sharding, and high-availability strategies for petabyte-scale data.

Performance, Reliability & DevOps

Observability & Optimization: Proven track record in performance monitoring and query tuning for distributed workloads to ensure system reliability and cost-efficiency.

Data Engineering Lifecycle: Experience designing and optimizing high-throughput ETL/ELT pipelines and ingestion systems (batch and streaming) using Spark.

Deployment & Orchestration: Experience building robust CI/CD pipelines for data infrastructure and deploying services using containerization (Docker, Kubernetes).

Security, Compliance & Domain Knowledge

Sensitive Data Handling: Expertise in building systems that handle protected information, with specific experience in HIPAA and SOX compliance frameworks.

Healthcare Data Expertise: Experience navigating health-tech data complexities, such as Electronic Health Records (EHR), clinical data formats (HL7/FHIR), and claims data.

Physical Requirements:

Sitting for prolonged periods of time. Extensive use of computers and keyboard. Occasional walking and lifting may be required.

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