Data Engineer

Value Technology Inc; Charlotte (NC); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Value Technology Inc. is seeking a Senior Data Engineer to design, build, and maintain scalable data platforms at our Charlotte, NC office. This role requires leadership in technical decisions and strong collaboration with stakeholders.

The candidate will work in a hybrid setup, with three days per week onsite, and contribute to data lake house architectures across Snowflake, Redshift or Synapse ecosystems.

Qualifications

• Design, build and maintain scalable data platforms.
• Lead technical decisions and architecture discussions.
• Experience with ETL/ELT pipelines and data modelling.

Responsibilities

• Architect and guide data solutions for analytics needs.
• Mentor junior engineers and review designs.
• Partner with product and business teams to align data strategy.

Skills

System design

Mentoring junior engineers

Stakeholder communication

Project estimation

Tools

Python

SQL

Scala/Java

Apache Spark

Hadoop ecosystem

Kafka

Airflow

AWS

Azure

Google Cloud

PostgreSQL

MySQL

NoSQL (MongoDB/Cassandra/DynamoDB)

Git

CI/CD

Docker

Kubernetes

Terraform

Delta Lake

DBT

Databricks

Job description

Job Title: Data Engineer
Location: Charlotte, NC (Hybrid - 3 days in a week)

Job Description:

Value Technology is seeking for a Senior Data Engineer role resource is required at onsite location (Charlotte, NC - North Carolina-USA Onsite location)). Resource will have to work from office for 3 days in a week. Resource is expected to design, build, and maintain scalable data platforms while leading technical decisions.

Key technical skills - required:

• Programming: Python (advanced), SQL (expert level), Scala or Java (often preferred for big data)
• Data Engineering skills required: ETL/ELT pipeline development, Data modelling (star schema, dimensional modelling), Data warehousing (Snowflake, Big-Query, Redshift, Synapse), Data lakes and lake-house architectures
• Big Data Technologies skills required: Apache Spark (essential), Hadoop ecosystem
• Kafka (streaming), Apache Airflow or similar workflow orchestration tools
• Cloud Platforms skills required: AWS (S3, Glue, EMR, Lambda, Redshift), Azure (ADF, Synapse, Databricks), Google Cloud (Big-Query, Dataflow, Data-proc)
• Databases skills required: PostgreSQL, MySQL, NoSQL databases (MongoDB, Cassandra, DynamoDB)
• DevOps & Engineering Practices: Git, CI/CD pipelines, Docker, Kubernetes, Infrastructure as
• Code (Terraform is a plus)
• Data Quality & Governance: Data validation and testing, Metadata management, Security and access control, Monitoring and observability
• Leadership Skills: System design and architecture, Mentoring junior engineers, Stakeholder communication
• Project estimation and technical planning

Nice-to-Have Skills

• Databricks
• DBT (Data Build Tool)
• Delta Lake or Apache Iceberg
• Machine learning data pipelines
• Generative AI and LLM data infrastructure