AWS Databricks Data Engineer

Lightning Minds Inc.
United States
5 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

Amazon Web Services Amazon S3 Automation of Tests Computer Programming Continuous Integration Information Engineering Data Governance Data Infrastructure Github Identity and Access Management Python (Programming Language) Machine Learning
+12 more
Medicaid Management Information Systems (MMIS) SQL Databases Data Streaming Data Storage Technologies Apache Spark Gitlab Data Lakes Pyspark Data Lakehouse Functional Programming Data Pipelines Databricks

Job description

  • Design and implement batch and streaming data pipelines using PySpark, Delta Lake, and Delta Live Tables (DLT).
  • Develop scalable ingestion and transformation solutions within Databricks.
  • Build integrations with AWS services such as S3, IAM, and Lambda.
  • Configure and manage data governance, security, and access controls via Databricks Unity Catalog.
  • Monitor and optimize pipeline performance, reliability, and data quality.
  • Automate testing and deployment using CI/CD tools (GitHub/GitLab).
  • Collaborate with data scientists and stakeholders to prepare datasets for analytics and machine learning.
  • Support healthcare payer datasets including claims, provider, member enrollment, and MMIS data.

Requirements

We are seeking an experienced AWS Databricks Data Engineer to design, build, and maintain scalable data pipelines and cloudnative data infrastructure. The ideal candidate will have strong expertise in Apache Spark, PySpark, Python, SQL, Delta Lake, and AWS services, with proven experience in production Databricks environments., * 3 5 years of handson data engineering experience.

  • Strong productionlevel experience with Databricks.
  • Advanced programming skills in Python and PySpark.
  • Advanced SQL expertise.
  • Deep understanding of Apache Spark, Delta Lake, and Data Lakehouse architecture.
  • Experience with Delta Live Tables, Unity Catalog, and Databricks Workflows.
  • Familiarity with AWS cloud services for data storage and management.

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