Senior Data Engineer

• Job Title: Data Engineer
• Description & Requirements:

This role is Hybrid in Charleston, SC (Occasional onsite when needed) & it’s a fulltime position.

KORE1, a nationwide provider of staffing and recruiting solutions, has an immediate opening for a Data Engineer in Charleston, SC.

• Position Overview
• We are seeking a highly capable Data Engineer to design and build the data infrastructure that powers investment operations, reporting, and business intelligence capabilities. This is a foundational role within a firm actively modernizing its data architecture by replacing fragmented automations with scalable, production-grade pipelines and establishing a centralized, reliable source of truth across multiple systems.

The Data Engineer will own the end-to-end data stack, including ingestion, transformation, modeling, data quality, and governance. This role requires deep technical expertise along with the ability to navigate a complex, multi-system financial data environment.

This position will play a central role in supporting the organization's evolving AI and analytics initiatives. The ideal candidate will help structure, govern, and optimize warehouse data to support future AI-enabled workflows and advanced reporting capabilities.

The Data Engineer will work closely with cross-functional teams including Operations, IT, business stakeholders, and external technology partners to ensure the data platform evolves in alignment with operational and strategic needs.

• Key Responsibilities
• Architecture & Infrastructure
• Evaluate and recommend scalable data architecture solutions, including warehouse and lakehouse strategies.
• Build and maintain a centralized cloud data warehouse environment.
• Design and maintain scalable ingestion pipelines across multiple operational and financial systems.
• Develop data structures and governance models that support analytics, reporting, and future AI-driven workflows.
• Ensure the data platform is designed with long-term scalability, security, and accessibility in mind.
• Data Modeling & Transformation
• Design and implement canonical data models across financial and operational datasets.
• Write and optimize complex SQL queries, transformations, and performance-tuned data workflows.
• Replace manual or lightweight automations with production-grade ETL/ELT pipelines using Python and cloud-native tooling.
• Integrations & APIs
• Build and maintain REST API integrations across third-party platforms and internal systems.
• Develop Python-based ingestion and transformation processes.
• Support orchestration and storage within a cloud environment using modern data engineering best practices.
• Data Quality, Governance & Security
• Implement validation frameworks, deduplication logic, monitoring, and exception handling processes.
• Configure role-based access controls and maintain auditability across the data environment.
• Document and maintain end-to-end data lineage and governance standards.
• Support compliance and security requirements for sensitive financial and operational data.
• Reporting & Documentation
• Deliver reporting-ready datasets supporting portfolio analytics, operational reporting, and business intelligence initiatives.
• Support BI tool integrations and semantic layer development for technical and non-technical users.
• Create and maintain documentation for architecture decisions, pipelines, and data dictionaries.
• Cross-Functional Collaboration
• Partner closely with Operations, IT, and leadership teams to align data infrastructure with business goals.
• Participate in ongoing technology and systems planning initiatives.
• Act as a key liaison between technical and business stakeholders to ensure data solutions meet organizational needs.

• Technical Requirements
• Advanced Python development for data engineering and automation
• Advanced SQL skills including performance optimization and complex transformations
• Strong experience with Snowflake or similar cloud data warehouse platforms
• Experience designing scalable data models and ETL/ELT pipelines
• REST API integration experience including authentication, pagination, and error handling
• Cloud platform experience, preferably AWS
• Strong understanding of data quality, governance, and access controls
• Ability to work cross-functionally in fast-paced environments

• Preferred Skills
• Experience supporting AI or LLM-enabled workflows
• Financial services, private equity, asset management, or investment operations experience
• Familiarity with CRM, fund administration, or portfolio management platforms
• Experience with BI tools such as Tableau, Looker, or Sigma

• Required Qualifications
• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical field
• 5+ years of experience in data engineering
• Strong production experience with Python and SQL
• Experience building scalable cloud-based data platforms
• Strong documentation and communication skills

Preferred

• Experience working with financial datasets and investment operations
• Exposure to AI-driven analytics or agent-based workflows
• Experience implementing enterprise reporting and business intelligence solutions

• Core Competencies
• Ownership and accountability
• Strong analytical and systems thinking
• Cross-functional collaboration
• Clear communication with technical and non-technical stakeholders
• Adaptability in fast-paced environments
• High standards for governance, accuracy, and compliance

Compensation depends on experience but is typically $145K-$160K