IT Data Engineer IV

🕒 August 18

🏈 Alabama, Colorado, +5 more states – Remote

🏈 Alabama – Remote ⛰️ Colorado – Remote 🐊 Florida – Remote 🌲 North Carolina – Remote 🌴 South Carolina – Remote 🤠 Texas – Remote ⚔️ Virginia – Remote

💵 $87.3k - $139.4k / year

⏰ Full Time

🟠 Senior

🔴 Lead

🚰 Data Engineer

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SouthState Bank

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

🏦 Banking

💸 Finance

💳 Fintech

Banking • Finance • Fintech

SouthState Bank is a financial institution that offers a wide range of banking products and services. It provides personal banking solutions such as checking and savings accounts, credit cards, and online and mobile banking. The bank also offers borrowing options including personal loans, mortgages, and home equity lines of credit. Additionally, SouthState Bank provides investment services like financial and retirement planning. For businesses, it offers small business and commercial banking services, including loans, lines of credit, and cash flow management. They also provide wealth management services for personal and corporate clients.

📋 Description

• Architect, design, and deliver enterprise data platform solutions using Snowflake, dbt, SQL, Python, and modern data integration technologies • Establish and enforce data engineering standards, best practices, and governance for code quality, CI/CD, testing, observability, documentation, metadata, security, and operational excellence • Partner with business stakeholders, data owners, architects, compliance teams, and technology partners to translate requirements into data solutions, models, integration patterns, and roadmaps • Lead support, monitoring, and continuous improvement of enterprise data platforms • Resolve complex production issues, improve performance and data quality, and ensure operational reliability • Provide technical leadership, mentorship, architectural reviews, coaching, technology evaluation, and strategic direction for the data engineering practice • Support advanced analytics, AI/ML, and enterprise data initiatives • Take ownership of tasks and challenges encountered in the assigned position

🎯 Requirements

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or related technical field, or equivalent combination of education and relevant professional experience • 8–10+ years of progressive data engineering experience, including at least 3 years in a senior or lead technical capacity • 5+ years designing, developing, and optimizing Snowflake solutions • 5+ years in a senior engineer, technical lead, solution lead, or architecture-influencing capacity • 5+ years hands-on experience with dbt • 5+ years of experience with SQL and Python • 3+ years of experience with pipeline orchestration tools • Experience partnering with business departments, data owners, reporting teams, architects, compliance, and technology groups • Experience supporting production data pipelines, troubleshooting data quality issues, root cause analysis, and monitoring or preventive controls • Demonstrated experience architecting ML/AI data infrastructure, including feature stores, MLOps pipelines, and LLM-based data processing workflows • Experience with streaming, lakehouse architecture, metadata management, data observability, or AI/ML data preparation preferred • Prior experience in financial services, banking, or another regulated industry strongly preferred • Preferred cloud data platform certification, such as AWS Certified Data Analytics – Specialty, Microsoft Certified: Azure Data Engineer Associate, GCP Professional Data Engineer, or Snowflake SnowPro • Preferred dbt Certification or equivalent analytics engineering credential • Expert-level ability with SQL, Python, Snowflake, dbt, and enterprise orchestration patterns • Strong production-grade engineering practices, including code reviews, version control, CI/CD, automated testing, documentation, monitoring, and incident response • Advanced dbt knowledge, including incremental models, snapshots, seeds, macros, tests, and multi-environment deployment strategies • Advanced hands-on Snowflake expertise, including schema design, access patterns, warehouse sizing, query optimization, data sharing, and cloud integrations • Proficiency with Snowflake, AWS Redshift, Azure Synapse Analytics, or GCP BigQuery • Experience with Delta Lake, Apache Iceberg, or Apache Hudi • Working knowledge of Azure, AWS, or GCP cloud data architecture • Proficiency with Docker and Kubernetes • Understanding of AI/ML data engineering, semantic models, feature data, feature stores, model-ready datasets, and analytical data products • Experience with unstructured data processing, semantic search, embeddings, and workflow orchestration • Knowledge of MLOps, model lifecycle support, monitoring, governance, drift awareness, and continuous improvement • Familiarity with orchestrating AI agent workflows and tool-calling patterns using MCP or similar technologies • Proficiency with real-time and event-driven data platforms, message streaming, event ingestion, pub/sub, and enterprise integrations • Experience with stream processing, change data capture, and incremental data movement • Strong understanding of data quality frameworks, observability, lineage tracking, metadata management, data cataloging, and data classification • Ability to design scalable, cost-optimized architectures using medallion, data vault, or dimensional modeling • Strong technical communication, analytical, facilitation, mentoring, and stakeholder-influence abilities • Ability to sit for extended periods and work extensively on a computer

🏖️ Benefits

• Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions • Secure and distraction-free remote or hybrid work setting required, with reliable internet connection (cable or fiber preferred) • Equal Opportunity Employer, including disabled/veterans