Lead Data Engineer

Role Overview

• The Lead Data Engineer designs, builds, and maintains data processing architectures and solutions enabling the efficient conversion of structured and unstructured data to insights at enterprise scale
• Ingests data from internal and external sources utilizing cloud native platforms and software development best practices and patterns
• Develops software tools that leverage artificial intelligence, machine learning, and big-data techniques to cleanse, organize, and transform data into insights and actions that enable Humana to better serve our members
• This lead will design and develop applications using Data engineering related tech
• Act as one of the primary point of contact for the team, build POCs, build quick prototypes with latest industry standard software libraries and scale it for the platform
• Design, code, test, debug and document programs using Agile development practices
• Provides the strategy and design for projects associated with their technology domain including, upgrades and deployments
• Develops new documentation and departmental technical procedures
• Makes decisions on moderately complex to complex issues regarding technical approach for project components, and work is performed without direction
• Exercises considerable latitude in determining objectives and approaches to assignments
• Troubleshoots business and production issues by gathering information (for example, issue, impact, criticality, possible root cause);
• engaging support teams to assist in the resolution of issues; formulating an action plan; performing actions as designated in the plan; interpreting the results to determine further action; performs root cause analysis to prevent future occurrence of issues; and completing online documentation
• Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, mentoring other members of the engineering community

Requirements

• 12 + years of Data engineering experience with Hands-on experience with Data Lakes, Event Streaming, Data Fabric, DevOps
• 8 + years of experience designing software applications using best practices and design first approach
• 8 + years of experience with Python, Azure Databricks, Pyshark, Snowflake
• Experience in event-based streaming using Kafka in various formats like Json or Avro
• Experience designing and developing cloud solutions using AWS, Azure or Google is a significant plus
• Experiencing leading engineering team/teams in end-to-end delivery
• Proficiency in federated data architectures (e.g., Data Mesh) and centralized models
• Strong experience with metadata management, data lineage, governance, discovery, and quality
• Experience in Database related tech like Oracle or Sql server
• Demonstrates a strong commitment to team success by proactively contributing and taking initiative to ensure the delivery of high-quality work
• Experience analyzing existing applications and making modifications for new features while maintaining other existing functionalities
• Experience working with GitHub and/or GitLab, SonarQube, JUnit, designing unit test cases using TDD and BDD methodologies
• Experience using CI/CD pipelines and code quality tools
• Test driven mindset using frameworks like Junit, SOAPUI, Selenium and contract testing tools
• Expert knowledge of the Agile methodologies
• Experience in Docker and Kubernetes

Tech Stack

• AWS
• Azure
• Cloud
• Docker
• JUnit
• Kafka
• Kubernetes
• Oracle
• Python
• Selenium
• SQL

Benefits

• medical, dental and vision benefits
• 401(k) retirement savings plan
• time off (including paid time off, company and personal holidays, volunteer time off, paid parental and caregiver leave)
• short-term and long-term disability
• life insurance and many other opportunities