Databricks Architect

Point C

3d•$100,000 - $120,000

About The Position

Point C is a National third-party administrator (TPA) with local market presence that delivers customized self-funded benefit programs. Our commitment and partnership means thinking beyond the typical solutions in the market – to do more for clients – and take them beyond the standard “Point A to Point B.” We have researched the most effective cost containment strategies and are driving down the cost of plans with innovative solutions such as, network and payment integrity, pharmacy benefits and care management. There are many companies with a mission. We are a mission with a company. We're looking for a Databricks Architect & Developer to design and build enterprise-scale data platforms supporting multiple claims systems. This role will own the end-to-end lakehouse architecture — from ingestion through governance — while partnering closely with data engineers, analysts, and business stakeholders to translate requirements into robust, production-ready technical solutions on Azure.

Requirements

5–7 years of data engineering/cloud experience.
Strong hands-on experience with Databricks and Apache Spark.
Advanced PySpark and SQL.
Strong understanding of Delta Lake and Medallion Architecture.
Experience with at least one cloud platform: Azure.
Knowledge of Data Governance, Unity Catalog, IAM/RBAC, and security.
Experience with Git, CI/CD, and infrastructure-as-code concepts.
Strong understanding of data warehousing, dimensional modeling, and distributed data processing.

Nice To Haves

Azure Data Factory
Terraform
Kafka or other streaming technologies
Power BI platforms
Databricks certifications
Experience designing enterprise data lakes/lakehouses

Responsibilities

Design and implement scalable data platforms using Databricks, Apache Spark, Delta Lake, and SQL, producing solution architecture and technical design documentation.
Develop Medallion Architecture (Bronze, Silver, Gold) for enterprise data workloads from multiple claim systems (VBA, Quicklink, HealthPac, and file-based TPAs).
Build and optimize production-grade ETL/ELT pipelines using Databricks Workflows, PySpark, and SQL.
Work with ADF+ADLS ingest and existing kill-and-fill dimension patterns.
Design and maintain data models and Delta tables, implementing schema evolution, time travel, partitioning, and optimization.
Design solutions on Azure, integrating cloud storage and databases.
Implement Unity Catalog, access controls, data governance, lineage, and security.
Translate claim-system data dictionaries into Unity Catalog tables for reporting and APIs.
Define and execute performance and cost-optimization strategies across the platform.
Work with data engineers, analysts, and business stakeholders to translate requirements into technical designs.
Establish CI/CD practices for Databricks notebooks, jobs, and infrastructure.
Troubleshoot production data pipelines and support platform reliability.