Sr. Data Engineer- Charlotte, NC

Matlen Silver; Charlotte (NC); Hybrid; USD 100,000 - 120,000; Full time

Job summary

Matlen Silver is looking for a Data Engineer in Charlotte, NC to deliver end-to-end data solutions for various business challenges. Ideal candidates should have 5+ years of experience in Data Engineering, proficiency in data warehousing and big data technologies, and a strong understanding of cloud platforms, preferably Google Cloud Platform (GCP). The position offers a hybrid work schedule with 3 days on-site and 2 remote while working on a contract basis for 8-9 months.

Qualifications

• 5+ years of experience in Data or BI Engineering.
• 4+ years of experience using Software Development Life Cycle (SDLC).
• 3+ years of experience with Google Cloud Platform (GCP).

Responsibilities

• Deliver data solutions addressing business problems.
• Translate business requirements into scalable designs.
• Evaluate build vs. buy decisions for platforms.

Skills

Data Warehousing/ETL

SQL

Cloud-based platforms

Big data technologies

Object-oriented programming

Analytical thinking

Education

Bachelor’s Degree in Engineering, Computer Science, or related field

Job description

Job Title: Data Engineer

Location: Charlotte NC 28203

Schedule: Hybrid (3 days on-site and 2 days remote)

Position: Contract

Duration: 8-9 month

Interview Mode: In person

Employment Type: W2

Job Overview

We are seeking a Data Engineer / Data Solutions Engineer to deliver end-to-end data solutions for simple to moderately complex business challenges. This role focuses on translating business needs into technical requirements, designing scalable architectures, and supporting the implementation and maintenance of robust data solutions. You will act as a technical expert, helping evaluate the right platforms and technologies while ensuring best practices are followed across reliability, scalability, performance, security, and long-term maintainability.

Key Responsibilities

• Deliver data solutions across multiple applications, resolving moderately complex business problems with limited guidance
• Translate business requirements into technical specifications and scalable solution designs
• Participate in planning, estimation, and mentoring junior engineers
• Evaluate build vs. buy decisions and recommend best-fit platforms and technology stacks
• Lead the design and development of scalable, flexible, and maintainable data and enterprise solutions
• Ensure adherence to architectural standards and best practices
• Develop and enforce testing strategies, including unit testing, integration testing, and support for user acceptance testing
• Define and implement data solutions aligned with business objectives, SLAs, data quality, and observability standards
• Collaborate with data governance teams on data retention, privacy, and security standards
• Partner with data science teams to support model deployment and scalability
• Analyze and structure data to support business insights and decision-making
• Design and build operational and analytical (including self-service) data applications
• Contribute to infrastructure initiatives including design, cost-benefit analysis, implementation, and support
• Evaluate design alternatives and manage trade-offs across risk, cost, and performance
• Work with networking and cloud concepts such as VPCs, subnetting, routing, security groups, and load balancing

Minimum Qualifications

• Bachelor’s Degree in Engineering, Computer Science, Computer Information Systems (CIS), or related field (or equivalent work experience)
• 5+ years of experience in Data or BI Engineering, Data Warehousing/ETL, or Software Engineering
• 4+ years of experience working on projects involving the implementation of solutions using Software Development Life Cycle (SDLC) methodologies
• 5+ years of experience in object-oriented or structured programming, SQL, and scripting
• 5+ years of experience with big data technologies
• 3+ years of experience with cloud-based big data platforms, preferably Google Cloud Platform (GCP)

Preferred Skills

• Strong understanding of data architecture and distributed systems
• Experience building scalable and reusable data frameworks
• Knowledge of data governance, data quality, and observability best practices
• Ability to collaborate across cross-functional teams including engineering, data science, and business stakeholders
• Strong analytical thinking and problem-solving skills