AAI Data Engineer – Enterprise Platform

FIS•Jacksonville, FL

1d•Remote

About The Position

FIS Management Services, LLC seeks an AAI Data Engineer – Enterprise Platform to design and develop financial technology platforms to enable data-driven decisions for finance and operations. This role involves building and optimizing enterprise-scale data pipelines and data warehousing solutions using Snowflake, ensuring performance, reliability, and cost efficiency. The engineer will write and tune complex SQL queries for large-scale data processing and implement advanced optimization strategies. A key part of the role includes administering Snowflake environments extensively, covering user roles, RBAC, privileges, access control, encryption, TSS key rotation, compliance checks, resource monitors, warehouse sizing, and replication strategies for high availability. Data governance measures such as masking policies, secure access controls, and encryption standards will be implemented. Automation of account and role management using identity protocols like SAML, SCIM, & OAuth is required, along with configuring storage/API integrations for seamless data ingress and egress, including Fivetran based ingestion pipelines. Collaboration with internal teams and external partners to migrate legacy systems to modern cloud platforms and deliver end-to-end data applications is expected. The role also focuses on optimizing OLAP/BI workflows for performance and cost-efficiency while maintaining data integrity. Security standards will be enforced, network policies configured, IP ranges managed, and encryption ensured for secure operations. Development of executive-level reports to support strategic decisions and cost optimization is also a responsibility. Integration of Databricks primarily as a data source for Snowflake pipelines is required. Building and maintaining ingestion workflows using PySpark and Delta Lake for secure, scalable data transfer into Snowflake is part of the role. Configuration of connections with Amazon S3 and Azure Data Lake Storage for efficient data movement, application of governance policies, and troubleshooting ingestion performance issues to ensure smooth transformation processes are also key duties. Maintaining high standards of security, compliance, and operational excellence across all data platforms is essential. The role will leverage Snowflake’s integrated AI capabilities—including Cortex functions, governance controls, and secure in platform execution—to apply AI directly on enterprise data without data egress and support enterprise Data & AI initiatives. Proficiency in cross-platform data integration and automation using APIs and cloud-native services is needed.

Requirements

Master’s degree or foreign equivalent in Applied Computer Science, Computer Science, Computer Engineering, or related field.
Three (3) years of experience in designing and optimizing data pipelines using SQL, Python, and Snowflake, including ELT/ETL and performance tuning.
Experience building scalable data processing workflows with Databricks and PySpark.
Experience administering cloud data environments with RBAC, identity integrations (SAML, SCIM, and OAuth), and security controls.
Experience deploying and managing data solutions in Azure and AWS, including S3/ADLS and API based data movement.
Experience applying data modeling and BI concepts, including fact/dimension modeling and semantic layer development.

Responsibilities

Design and develop financial technology platforms to enable data-driven decisions for finance and operations.
Build and optimize enterprise-scale data pipelines and data warehousing solutions using Snowflake, ensuring performance, reliability, and cost efficiency.
Write and tune complex SQL queries for large-scale data processing and implement advanced optimization strategies.
Administer Snowflake environments extensively, including user roles, RBAC, privileges, access control, encryption, TSS key rotation, compliance checks, resource monitors, warehouse sizing, and replication strategies for high availability.
Implement data governance measures such as masking policies, secure access controls, and encryption standards.
Automate account and role management using identity protocols including SAML, SCIM, & OAuth.
Configure storage/API integrations for seamless data ingress and egress including Fivetran based ingestion pipelines.
Collaborate with internal teams and external partners to migrate legacy systems to modern cloud platforms and deliver end-to-end data applications.
Optimize OLAP/BI workflows for performance and cost-efficiency while maintaining data integrity.
Enforce security standards, configure network policies, manage IP ranges, and ensure encryption for secure operations.
Develop executive-level reports to support strategic decisions and cost optimization.
Integrate Databricks primarily as a data source for Snowflake pipelines.
Build and maintain ingestion workflows using PySpark and Delta Lake for secure, scalable data transfer into Snowflake.
Configure connections with Amazon S3 and Azure Data Lake Storage for efficient data movement.
Apply governance policies and troubleshoot ingestion performance issues to ensure smooth transformation processes.
Maintain high standards of security, compliance, and operational excellence across all data platforms.
Leverage Snowflake’s integrated AI capabilities—including Cortex functions, governance controls, and secure in platform execution—to apply AI directly on enterprise data without data egress and support enterprise Data & AI initiatives.
Utilize cross-platform data integration and automation using APIs and cloud-native services.