Data Engineer

Talentify; Wilmington (MA); Remote; USD 76,000 - 90,000; Full time

Job summary

Talentify is seeking a Data Engineer to support the development and optimization of scalable data infrastructure powering high-volume, data-intensive applications. The role emphasizes building robust data pipelines and backend services for distributed systems.

You will work in a fully remote or hybrid setup, collaborating with engineering teams, using Docker and CI/CD, and improving data workflows for reliability and performance.

Qualifications

• 3+ years in infrastructure and software engineering with exposure to data engineering.
• Strong proficiency in SQL across relational databases and lakehouse environments.
• Experience building and supporting backend services in distributed systems.
• Hands-on experience with CI/CD pipelines (e.g., GitHub, Jenkins) and containerization (Docker).
• Proficiency in Python, C#, Kafka, shell scripting, and Linux/Unix systems.
• Proven ability to work independently and proactively in a remote environment.

Responsibilities

• Design, build, and maintain robust data pipelines for large-scale, distributed systems
• Develop and support backend services for high-throughput, data-intensive applications
• Optimize and manage SQL queries across both traditional RDBMS and modern lakehouse architectures
• Collaborate with engineering teams to deploy scalable services using Docker and CI/CD pipelines
• Monitor, troubleshoot, and improve data workflows to ensure reliability and performance
• Contribute to infrastructure automation and deployment processes
• Work independently to solve technical challenges while maintaining clear communication with stakeholders

Skills

SQL

Python

C#

Docker

CI/CD

Kafka

Shell scripting

Linux/Unix

Distributed systems

Tools

GitHub

Jenkins

Job description

Data Engineer

55.00 to 65.00 per hour

Hybrid Preferred/ Remote possible

About the Role

We're seeking a Data Engineer to support the development and optimization of scalable data infrastructure powering high-volume, data-intensive applications.

Key Responsibilities

• Design, build, and maintain robust data pipelines for large-scale, distributed systems
• Develop and support backend services for high-throughput, data-intensive applications
• Optimize and manage SQL queries across both traditional RDBMS and modern lakehouse architectures
• Collaborate with engineering teams to deploy scalable services using Docker and CI/CD pipelines
• Monitor, troubleshoot, and improve data workflows to ensure reliability and performance
• Contribute to infrastructure automation and deployment processes
• Work independently to solve technical challenges while maintaining clear communication with stakeholders

Required Qualifications

• 3+ years of experience in infrastructure and software engineering with exposure to data engineering
• Strong proficiency in SQL across relational databases and lakehouse environments
• Experience building and supporting backend services in distributed systems
• Hands-on experience with CI/CD pipelines (e.g., GitHub, Jenkins) and containerization (Docker)
• Proficiency in Python, C#, Kafka, shell scripting, and Linux/Unix systems
• Proven ability to work independently and proactively in a remote environment

Preferred Qualifications

• Experience with Java
• Familiarity with cloud storage solutions (e.g., blob/object storage)
• Experience with infrastructure-as-code tools such as Terraform
• Exposure to Kubernetes for container orchestration
• Experience with workflow orchestration tools (e.g., Airflow, Cloud Composer)
• Familiarity with Apache Beam or similar data processing frameworks

What Success Looks Like

• Delivery of reliable, scalable data pipelines within the contract period
• Improved performance and stability of data systems
• Effective collaboration in a remote, fast-paced engineering environment
• Clear documentation and maintainable code for long-term usability

Work Environment

• Fully remote, asynchronous-friendly team
• High-impact role contributing to cutting-edge automation and data systems
• Opportunity to work with modern data infrastructure and distributed architectures