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, LakeBase 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

Skills

• Must have

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 solutions
• 5 + years of experience in Python
• 3+ 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 Bus
• 2+ 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 DevOps automation with Terraform.
• Experience with CI/CD process and tools – GitHub 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 LLMs

• Ability 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

• Nice to have

• Exceptional communication skills.

• Ability to deliver exceptional customer service with a positive attitude.

• Other

• Languages

• English: C1 Advanced

• Seniority

• Senior

• Remote United States, United States of America

• Information Governance (Application)

• Cross Industry Solutions

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