Application Developers | Data engineers

Project description Join Our Team:
Innovating Health Care with Cutting-Edge Technology Responsibilities

• Primary Responsibilities:
  
  Design and develop ETL/ELT solutions on Azure Databricks, Lake Base and Spark Develop, implement, and deploy large scale data pipelines empowering machine learning algorithms, insights generation, business intelligence dashboards, reporting and new data products
  
  Design, build, optimize, and manage modern large-scale data pipelines ETL/ELT processing to support data integration for analytics, machine learning features and predictive modelling
  
  Consume data from a variety of sources (RDBMS, APIs, FTPs and other cloud storage) & formats (Excel, CSV, XML, JSON, Parquet, Unstructured)
  Write advanced / complex SQL with performance tuning and optimization
  
  Build AI based solutions for solving business needs, process automations and improving operational efficiency
  
  Identify ways to improve data reliability, data integrity, system efficiency and quality
  
  Participate in architectural evolution of data engineering patterns, frameworks, systems, and platforms including defining best practices and standards for managing data collections and integration
  
  Mentor other data engineers and provide technical direction by teaching other data engineers how to leverage cloud data platforms

• Required Qualifications:
  
  7 + years of experience in data engineering, data integration, data modeling, data architecture, and ETL/ELT processes to provide quality data and analytics solutions5 + years of experience in Python3+
  
  Experience with API design and lifecycle management (GraphQL, REST, etc.)2 + years Hands-on experience with Redis-backed state management and event-driven processing.
  2 + years of experience in Apache Spark (PySpark/Spark SQL)2+ years building and deploying Cloud based solutions using - Azure Databricks with UC, Snowflake, Functions, Service Bus2+ years of experience in SQL with designing complex data schemas and query performance optimization
  
  Experience building LLM integrations for workflow automation/business needs.
  
  Experience with Dev Ops automation with Terraform.
  
  Experience with CI/CD process and tools – Git Hub Actions, GIT, Artifactory, Sonar
  
  Preferred Qualifications:
  
  Bachelor’s degree in Computer Science, Engineering, Mathematics or related discipline
  
  Extensive knowledge of data architecture principles (e.g., Data Lake, Databricks Delta Lake, Data Warehousing, etc.)Extensive knowledge of data modelling techniques including slowly changing dimensions, aggregation, partitioning and indexing strategies
  
  Experience working with LLMsAbility to independently troubleshoot and performance tune large scale enterprise systems
  
  Excellent collaborator with experience working effectively with cross-functional teams such as leadership, product management and engineering, with a willingness to inspire other data engineers, data scientists and analysts
  
  Solid communication skills with the ability to communicate technical concepts to both technical and non-technical audiences

Exceptional communication skills.

Ability to deliver exceptional customer service with a positive attitude.