Senior Data Engineer

Overview

This is a remote role that may only be hired in the following location(s): North Carolina, Arizona, Florida and Texas.

We are seeking an experienced Senior Data Engineer to join our Data Platform Engineering Organizationand help build scalable cloud-based data solutions that enable analytics and data-driven decision-making across the organization.

The ideal candidate is a hands-on data engineer with expertise in cloud-based data platforms, data warehousing, ETL/ELT development, and modern data engineering practices. This individual will build and optimize scalable data pipelines, integrations, and data products utilizing AWS Services, Snowflake, dbt, Python, SQL, and related technologies.

As part of our growing Cloud Data & AI Platform organization, you will collaborate with a talented team of engineers, product partners, and business stakeholders to deliver cloud-based data solutions that support critical business initiatives. This is an opportunity to work with modern technologies, solve complex data challenges, and contribute to enterprise-scale data platforms that enable data-driven decision-making across the bank.

Responsibilities & Qualifications

Duties & Responsibilities:

Data Architecture and Strategy - Design and implement scalable, efficient data architectures. Lead the development of data strategy aligned with business objectives. Evaluate and integrate new technologies to enhance data capabilities

Advanced Data Pipeline Development - Architect and implement complex data pipelines for real-time and batch processing. Optimize data flows for high-volume, high-velocity data environments. Develop advanced ETL processes for diverse data sources.

Data Governance and Quality Management - Establish and enforce data governance policies and best practices. Implement data quality frameworks and monitoring systems. Ensure compliance with data regulations and standards

Performance Optimization and Troubleshooting - Analyze and optimize system performance for large-scale data operations. Troubleshoot complex data issues and implement robust solutions

Mentorship and Knowledge Sharing - Mentor junior data engineers and provide technical guidance. Contribute to the development of best practices and standards. Collaborate with cross-functional teams to drive data literacy.

Qualifications:

Bachelor's Degree and 4 years of experience in Data Engineering, Data Warehousing, Cloud Data Platforms, or related technology disciplines.

OR

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.

Additional Information

Benefits are an integral part of total rewards and First Citizens Bank is committed to providing a competitive, thoughtfully designed and quality benefits program to meet the needs of our associates. More information can be found at https://jobs.firstcitizens.com/benefits.

Benefits are an integral part of total rewards and First Citizens Bank is committed to providing a competitive, thoughtfully designed and quality benefits program to meet the needs of our associates. More information can be found at https://jobs.firstcitizens.com/benefits.

Duties & Responsibilities:

Data Architecture and Strategy - Design and implement scalable, efficient data architectures. Lead the development of data strategy aligned with business objectives. Evaluate and integrate new technologies to enhance data capabilities

Advanced Data Pipeline Development - Architect and implement complex data pipelines for real-time and batch processing. Optimize data flows for high-volume, high-velocity data environments. Develop advanced ETL processes for diverse data sources.

Data Governance and Quality Management - Establish and enforce data governance policies and best practices. Implement data quality frameworks and monitoring systems. Ensure compliance with data regulations and standards

Performance Optimization and Troubleshooting - Analyze and optimize system performance for large-scale data operations. Troubleshoot complex data issues and implement robust solutions

Mentorship and Knowledge Sharing - Mentor junior data engineers and provide technical guidance. Contribute to the development of best practices and standards. Collaborate with cross-functional teams to drive data literacy.

Qualifications:

Bachelor's Degree and 4 years of experience in Data Engineering, Data Warehousing, Cloud Data Platforms, or related technology disciplines.

OR

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.