> Markdown version of [/jobs/ext/4565247-senior-data-engineer-data-modeler](https://www.wearedevelopers.com/jobs/ext/4565247-senior-data-engineer-data-modeler). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer / Data Modeler - **Company:** EXECUTIVE RECRUITERS - **Location:** Atlanta, GA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Third Normal Form, Amazon Web Services, Microsoft Azure, Cloud Computing, Information Systems, Databases, Data as a Services, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Warehousing, IBM InfoSphere DataStage, Dimensional Modeling, Payment Systems, Fraud Prevention and Detection, PCI Data Security Standards, Cloud Services, Software Engineering, SQL Databases, Data Streaming, Talend, Informatica Powercenter, Snowflake, Git, Containerization, Kubernetes, Information Technology, Star Schema, Apache Kafka, Data Management, Api Design, Azure Synapse Analytics, Software Version Control, Data Pipelines, Docker, Amazon Redshift, Databricks, Programming Languages - **Published:** November 4, 2026 - **Apply:** https://www.careerbuilder.com/job-details/senior-data-engineer-data-modeler-atlanta-ga--d45b17b8-2cc9-4db6-8f23-7867ddfaf3a0 ## About the Role Data Modeling, Software Engineering, Reconciliation, Data Management, Cloud Computing, Banking Services, Regulatory Reports, Payment Processing, Database Extract Transform and Load (ETL), Data Modeling, Bachelor's degree in Computer Science, Information Systems, or a related field (or equivalent experience). 7+ years of experience in data engineering/data modeling within financial services or banking. 7+ years of strong knowledge regarding payments domain concepts (auth, clearing, settlement, reconciliation, chargebacks, fraud). 7+ years of hands-on experience with data modeling techniques (3NF, star/snowflake schemas, dimensional modeling). 7+ years of proficiency in SQL and familiarity with an ETL/ELT tool (DataStage, Informatica, Talend, dbt). 7+ years of experience with cloud data platforms (AWS Redshift, Azure Synapse, Snowflake, Databricks). 7+ years of proficiency in a programming language such as Python for data processing and automation. 7+ years of experience with real-time streaming technologies (Kafka, Kinesis, EventHub) and batch data pipelines. 7+ years of familiarity with version control (Git) and CI/CD pipelines. Preferred Skills: Knowledge of regulatory and compliance requirements in payments/banking. Understanding of API-based integration for payment systems. Familiarity with containerization (Docker, Kubernetes) for data services deployment. ## Description We are seeking a talented Senior Data Engineer / Data Modeler focused on the payments subsystem to enhance our banking technology team. This role involves designing, developing, and maintaining scalable data pipelines and models for real-time and batch payment processing, settlement, reconciliation, and regulatory reporting. The ideal candidate will possess strong expertise in data modeling, ETL development, cloud data platforms, and modern data engineering practices., Design and implement logical and physical data models pertaining to payments (merchant onboarding, transactions, clearing, settlement, funding, fraud/risk, reporting). Develop ETL/ELT pipelines to integrate data from core banking systems, payment gateways, and external partners into enterprise data stores. Guarantee data quality, lineage, and governance across payment processing flows. Create and optimize data warehouses/lakes on cloud platforms like AWS or Azure. Collaborate with architects, developers, and business analysts to align payment business processes with data models and schemas. Implement real-time and batch data integration for critical applications such as fraud detection, reconciliations, settlement reporting, and regulatory compliance. Monitor and optimize pipelines for scalability, performance, and cost efficiency. Partner with security and compliance teams to enforce data privacy and regulatory requirements (PCI-DSS, SOX, AML/KYC).