IT Data Engineer IV

southstatebank; United States; On-site; USD 120,000 - 160,000; Full time

Job summary

The SouthState Bank is seeking an IT Data Engineer IV to lead enterprise data engineering efforts, building scalable data platforms, Snowflake solutions, and dbt-based transformation frameworks to support analytics and decision making.

The role mentors engineers, drives data quality, and partners with stakeholders across governance, compliance, and technology to deliver durable data solutions aligned with enterprise architecture. Strong leadership and technical depth are essential.

Qualifications

• 8-10+ years in data engineering with 3+ years in senior/lead roles.
• 5+ years using Snowflake including data modeling and performance tuning.
• 5+ years in senior engineer, technical lead, or architecture-influencing roles.
• 5+ years with SQL and Python for data engineering and data quality.
• 3+ years with pipeline orchestration tools.
• Experience with banking or regulated industries preferred.

Responsibilities

• Architect and deliver enterprise data platform solutions using Snowflake, dbt, SQL, Python.
• Set data engineering standards, governance, CI/CD, and observability.
• Translate business needs into data models and implementation roadmaps.
• Lead monitoring and continuous improvement of data platforms; resolve issues.
• Provide technical leadership, mentorship, and evaluate new technologies.
• Support AI/ML initiatives and enterprise data strategy.

Skills

Snowflake

dbt

SQL

Python

data modeling

CI/CD

data governance

data observability

AI/ML

leadership

Education

Bachelor's degree in Computer Science or related

Master's degree (preferred)

Tools

dbt

CI/CD tooling

SQL tooling

Job description

The SouthState story is one of steady growth, deep community roots, and an unwavering commitment to helping our customers move forward. Since our beginnings in the 1930s to becoming a trusted financial partner across the South and beyond - we are known for combining personal relationships with forward-thinking solutions.

We are committed to helping our team members find their success while maintaining the integrity of our values: building trust, fostering lasting relationships and pursuing excellence. At SouthState, individual contributions are recognized, potential is cultivated and team members are inspired to achieve their greater purpose. Your future begins here!

Summary

The IT Data Engineer IV serves as a senior technical lead for enterprise data engineering, responsible for designing, building, and improving scalable data platforms, Snowflake data solutions, and dbt-based transformation frameworks that support analytics, reporting, and operational decision-making across South State Bank. This role leads complex data engineering efforts, establishes standards for reliable and well-documented pipelines, and partners closely with business departments, data owners, architects, compliance, and technology teams to translate business needs into durable data solutions. The Data Engineer IV also mentors other engineers, drives continuous improvement in data quality and observability, and ensures data solutions align with enterprise architecture, governance, and regulatory expectations.

Duties & Responsibilities

• Architect, design, and deliver enterprise data platform solutions leveraging Snowflake, dbt, SQL, Python, and modern data integration technologies, ensuring scalable, secure, reliable, and maintainable data pipelines and analytical data products.
• Establish and enforce data engineering standards, best practices, and governance frameworks for code quality, CI/CD, data testing, observability, documentation, metadata management, security, and operational excellence.
• Partner with business stakeholders, data owners, architects, compliance teams, and technology partners to translate business requirements into data solutions, data models, integration patterns, and implementation roadmaps that deliver measurable business value.
• Lead the support, monitoring, and continuous improvement of enterprise data platforms by resolving complex production issues, improving performance, enhancing data quality, and ensuring operational reliability.
• Provide technical leadership, mentorship, and strategic direction for the data engineering practice, including architectural reviews, coaching engineers, evaluating emerging technologies, and supporting advanced analytics, AI/ML, and enterprise data initiatives.
• It is the responsibility of this role to take ownership of all tasks and challenges that they encounter in the operation of their assigned position. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Qualifications

Education Requirements

• Minimum: Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related technical field, or equivalent combination of education and relevant professional experience.
• Preferred: Master's degree in Computer Science, Data Engineering, Information Systems, Data Science, or related discipline.

Minimum Experience

• 8-10+ years of progressive data engineering experience, with at least 3 years in a senior or lead technical capacity.
• 5+ years of hands‑on experience designing, developing, and optimizing solutions in Snowflake, including SQL development, data modeling, performance tuning, security/access patterns, and production support.
• 5+ years serving in a senior engineer, technical lead, solution lead, or architecture‑influencing capacity.
• 5+ years of hands‑on experience with dbt, including model development, testing, documentation, macros, environment promotion, and CI/CD integration.
• 5+ years of experience with SQL and Python for data engineering, automation, transformation, and data quality validation.
• 3+ years of experience with pipeline orchestration tools.
• Experience partnering directly with business departments, data owners, reporting teams, architects, compliance, and other technology groups to gather requirements, communicate design decisions, and deliver production data solutions.
• Experience supporting production data pipelines, troubleshooting data quality issues, conducting root cause analysis, and implementing monitoring or preventive controls.
• Experience with streaming, lakehouse architecture, metadata management, data observability, or AI/ML data preparation is preferred.
• Demonstrated experience architecting ML/AI data infrastructure including feature stores, MLOps pipelines, and LLM-based data processing workflows.
• Prior experience in financial services, banking, or another regulated industry is strongly preferred.

Licenses & Certifications

• Preferred: Cloud data platform certification