Data Engineer

World Finance•Greenville, SC

About The Position

The Data Engineer implements data-centric solutions to complex business problems. This individual will work alongside a data architect and the data engineering team to expand and optimize data delivery architecture. Providing expertise in data warehousing and data delivery, this individual will work with cross-functional teams including marketing, analytics, operations, and software engineering to build data-aware systems and process flows across the enterprise. Essential Duties and Responsibilities: Protect confidential company information and ensure all data pipelines comply with enterprise security and privacy standards. Assist business, technology, and support partners/stakeholders to deliver secure data solutions. Design, build, and maintain data delivery solutions in accordance with governing data architecture patterns. Model and assemble data sets that meet functional and technical business requirements and AI feature needs . Implement and manage the infrastructure required to optimize ETL/ELT operations, including automated data preprocessing for analytics and AI model consumption. Process file-based data extracts and API integrations using modern data management tools to provide timely loading of critical business data Identify, design, and implement process improvements in data flows and data pipelines, focusing on automating data tasks. Integrate external systems with internal systems to ensure proper data flow between systems including AI services. Maintain an accurate inventory of data assets, storage systems, and data lineage to support transparency in AI-driven decision-making Communicate with non-technical stakeholders to determine technical solutions to business problems.

Requirements

Expertise with relational databases and advanced SQL proficiency.
Python skills for building and refining data pipelines, with a focus on libraries for data manipulation
Experience working with enterprise-scale data warehousing systems, supporting both internal and customer-facing applications with near real-time transactional data
Expertise in creating and maintaining data structures in SQL.
Experience structured and non-structured data paradigms, relational databases, data lake and data warehouse technologies, data vault and dimensional data models.
Ability to define problems, collect data, establish facts, and draw valid conclusions
Ability to conduct research into systems issues and emerging data engineering technologies and AI/ML tools to determine integration requirements
Ability to communicate ideas in both technical and user-friendly language.
Ability to work with IT operations to quickly come to resolution of open support requests
Self-motivated and able to work within a project-based environment.
Possesses strong oral and written communication skills, clearly and accurately communicating complex and/or technical information to both technical and nontechnical audiences.
Bachelor’s Degree in MIS, Computer Science, or related field, or equivalent professional experience.
Minimum 2 years of designing and implementing Data engineering solutions.
Hands on experience with building productionized data ingestion and processing pipelines.
Experience working in business intelligence and data warehousing environments.
Experience with MS SQL Server, Integration Services (SSIS)
Strong TSQL scripting abilities and understanding of complex stored procedures, views, data. aggregation/manipulation through table joins/queries, database design, normalization, and de-normalization techniques.
Demonstrated experience in high-volume data extraction, manipulation, and Bulk Loading ETL/ELT techniques
Industry experience working with large data sets.

Nice To Haves

Familiarity with data preprocessing for AI , including feature engineering, data cleansing for model training, and supporting prompt engineering workflows
Experience with Microsoft PowerBI is a plus, experience with a business intelligence and reporting platform preferred.
Familiarity with data preprocessing for AI/ML and supporting data structures for LLMs is a plus (Optional)

Responsibilities

Protect confidential company information and ensure all data pipelines comply with enterprise security and privacy standards.
Assist business, technology, and support partners/stakeholders to deliver secure data solutions.
Design, build, and maintain data delivery solutions in accordance with governing data architecture patterns.
Model and assemble data sets that meet functional and technical business requirements and AI feature needs
Implement and manage the infrastructure required to optimize ETL/ELT operations, including automated data preprocessing for analytics and AI model consumption.
Process file-based data extracts and API integrations using modern data management tools to provide timely loading of critical business data
Identify, design, and implement process improvements in data flows and data pipelines, focusing on automating data tasks.
Integrate external systems with internal systems to ensure proper data flow between systems including AI services.
Maintain an accurate inventory of data assets, storage systems, and data lineage to support transparency in AI-driven decision-making
Communicate with non-technical stakeholders to determine technical solutions to business problems.