AWS Data Engineer- Databricks & Healthcare Exp.

As a Data Engineer you ll design, build, and maintain scalable data pipelines using AWS and Databricks.

Summary:

Senior-level engineer responsible for designing, building, and supporting cloud-based data pipelines and health insurance applications using AWS and Databricks. Role involves complex system integrations, data engineering, and working closely with distributed agile teams.

Required:

10+ years experience designing and architecting solutions from scratch Strong expertise in AWS Cloud Services , including: Glue, ECS/EKS, Fargate Aurora, DocumentDB S3, Lambda, SNS, IAM, ECR Databricks expertise: Delta Live Tables (DLT) SQL, Spark, Python/PySpark Java Databricks workflows or Apache Airflow Strong understanding of: Data integration strategies

ETL / ELT

techniques Data warehousing principles Data transformation, quality, and observability Experience with DevOps practices , design patterns, and performance tuning Familiarity with

BI & Governance Tools :

Tableau Alation, Collibra Duties:

Design, build, and maintain scalable data pipelines using AWS and Databricks Implement ETL/ELT processes to load data into data lakes and downstream systems Ensure data quality, accuracy, reliability, and observability Build and automate unit, integration, and performance tests Integrate internal systems, external vendors, mobile apps, and data marts Support and enhance retail health insurance applications Monitor pipelines and proactively resolve production issues Participate in all SAFe/Agile ceremonies Collaborate with engineering, business, architecture, security, and infrastructure teams

Desired:

Migration of large-scale onprem data pipelines to Databricks (cloud) Experience with: Delta Lake, Iceberg, Apache Hudi Partitioning strategies & metadata management JSON/XML, document databases, real-time ingestion Lakehouse architecture, dimensional modeling,

Data Vault Skills: