Data Engineer
Role details
Job location
Tech stack
Job description
Hands-On Architecture and Engineering : Engage in hands-on architecture and engineering tasks. It is key for this role to have an in-depth understanding of cloud application deployment architectures using container management services such as Kubernetes and Amazon's EKS service. This may also expand into other areas such as data governance, data platform development/management, data engineering and pipelining, and framework development/adoption.
Backlog Prioritization and Resource Assignment: Interface directly with teams to understand their priorities and assign resources accordingly. Ensure alignment with goals and objectives.
Conduit Between Teams: Act as a bridge between various teams and NTT DATA's Data Practice. Identify opportunities where NTT DATA can provide additional thought leadership and support.
Innovation and Automation : Ideate on innovation opportunities in the data management space. Apply GenAI and other automation techniques to improve productivity and enhance solution maturity.
Requirements
NTT DATA is seeking an experienced Data Engineer to join our innovative Data Village team. This role is based on-site in either Plano, TX or Nashville, TN and supports a dynamic, high-performing team delivering cutting-edge data solutions. The ideal candidate will bring 10+ years of data engineering experience, with strong proficiency in Java and Python. We are looking for a self-directed engineer who can drive platform capabilities with minimal oversight, particularly across EKS infrastructure, platform engineering, and ModelOp platform management., * Experience: 10+ years of experience in team and technical leadership roles.
- Technical Skills: Strong background in data architecture and engineering, with experience in supporting legal, risk, compliance, finance, and HR functions. Proficiency with 10+ years experience in the following areas:
- Data Integration: Proficiency in integrating data from various sources.
- Relational Databases : Strong knowledge of relational databases.
- Data Pipelines : Experience in building and managing data pipelines.
- Programming (Java and Python ): Advanced skills in Java, Python and development of models for data science enablement.
- Kubernetes: Proficiency in using Kubernetes for container orchestration (AWS EKS is preferred). Having deep knowledge of Helm Chart configurations, including how to manage up/down scaling and application security in a microservices architecture.
- AWS : Strong knowledge of AWS services.
- Prometheus/JMeter/similar tools : Experience in creating application monitoring services.
- GitHub: Proficiency in using GitHub for version control.
- Jenkins: Experience in using Jenkins for continuous integration and delivery.
- Terraform: Strong knowledge of Terraform for infrastructure as code.
- Leadership Skills: Proven ability to mentor and coach data engineers, with a focus on best practices and continuous improvement.
- Communication Skills : Excellent communication and interpersonal skills, with the ability to interface directly with teams and understand their needs.
- Innovation Mindset: Ability to think creatively and identify opportunities for innovation and automation in the data management space.
Work Schedule: Ability to work on-site 5 days a week
