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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer - **Company:** First Citizens - **Location:** Jacksonville, FL, United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Business Analytics Applications, Data Analysis, Microsoft Azure, Big Data, Cloud Computing, Cloud Database, Software Quality, Continuous Integration, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Systems, Data Vault Modeling, Data Warehousing, IBM InfoSphere DataStage, Python (Programming Language), Operational Data Store, Productivity Software, Power BI, Cloud Services, DataOps, SAP (Applications), SQL Databases, SQL Server Integration Services, Data Streaming, Tableau (Software), Snowflake, Apache Spark, Change Data Capture, Apache Flink, Deployment Automation, Data Analytics, Qlikview, Real Time Data, Apache Kafka, Data Pipelines - **Published:** July 24, 2026 - **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/17694554?backUrl=%2Fcareer%2F17694554%2FSenior-Data-Engineer-Florida-Jacksonville ## About the Role Bachelor's Degree and 4 years of experience in Data Engineering, Data Warehousing, Cloud Data Platforms, or related technology disciplines., High School Diploma or GED and 8 years of experience in Data Engineering, Data Warehousing, Cloud Data Platforms, or related technology disciplines. Preferred Qualifications * Advanced experience with cloud platforms such as AWS, Azure, or GCP. * Advanced experience with modern data warehousing and large-scale data processing technologies such as Snowflake, Spark, or equivalent platforms. * Advanced proficiency in Python and SQL. * Advanced experience developing and supporting ETL/ELT processes, data pipelines, and data integration solutions utilizing tools such as dbt, Apache Airflow, Astronomer or equivalent cloud-native data engineering technologies. * Experience with data modeling, data warehousing, and data engineering best practices. * Experience designing, developing, and supporting scalable and reliable data engineering solutions in enterprise environments. * Experience collaborating with business and technology stakeholders to deliver data-driven solutions. * Strong analytical, problem-solving, and communication skills. Additional qualifications are a plus * Intermediate experience with enterprise ETL/ELT tools such as DataStage, SAP BODS, SSIS, Informatica, or equivalent technologies. * Intermediate experience developing and supporting Operational Data Stores (ODS), analytics platforms, and data products. * Intermediate experience with Change Data Capture (CDC), streaming, and real-time data ingestion technologies such as Kafka, Amazon Kinesis, Apache Flink, Qlik Replicate, Snow pipe Streaming, or equivalent platforms. * Intermediate experience integrating data across cloud and on-premises environments. * Experience with Data Vault modeling and modern data warehousing methodologies. * Intermediate understanding of data governance, security, compliance, and data quality management practices. * Experience working within Financial Services, Banking, or other highly regulated industries. * Familiarity with Tableau, Power BI, or other analytics and visualization platforms. * Experience using AI-powered development and productivity tools to improve engineering efficiency and delivery outcomes. * AWS Certified Data Engineer - Associate, AWS Certified Developer - Associate, SnowPro Core Certification, SnowPro Advanced Data Engineer Certification, or equivalent cloud and data platform certifications. ## Description The successful candidate will thrive in a collaborative environment, possess strong problem-solving skills, and be passionate about building reliable, scalable, and high-quality data solutions. * Design, develop, and support scalable data pipelines, data warehouses, and cloud-based data solutions utilizing AWS Services, Snowflake, dbt, Python, SQL, and related technologies. * Develop and maintain ETL/ELT processes, data integrations, and transformation frameworks supporting operational, reporting, and analytical workloads. * Implement and enhance data quality controls, reconciliation processes, testing frameworks, and dbt tests to ensure trusted and reliable data assets. * Optimize data pipeline performance and operational efficiency through monitoring, alert investigation, automation, testing, CI/CD, dashboard development, and production support activities. * Develop monitoring dashboards and operational metrics to improve platform visibility, reliability, and incident response. * Support deployment automation, release validation, and environment promotion processes to improve delivery reliability and operational efficiency. * Collaborate with business and technology stakeholders to understand requirements and deliver scalable data solutions that support business objectives. * Contribute to engineering best practices through technical discussions, peer reviews, documentation, and continuous improvement initiatives across the data engineering team * Leverage AI-powered development and productivity tools to improve engineering efficiency, code quality, testing, and delivery outcomes. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [REST, GraphQL, gRPC, and more: A comparison of modern API styles](https://www.wearedevelopers.com/videos/100247-rest-graphql-grpc-and-more-a-comparison-of-modern-api-styles) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Data Analytics with Microsoft Fabric: End-to-End Use Case with Data Agents](https://www.wearedevelopers.com/videos/1547-data-analytics-with-microsoft-fabric-end-to-end-use-case-with-data-agents) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)