• Ensure successful migration of structured and unstructured content—including PDFs, images, and custom repository artifacts—into the target system (xECM or equivalent) • Design, develop, and execute ETL/ELT processes tailored for PeopleSoft data and custom repository content • Identify and resolve migration issues related to PeopleSoft data structures, custom repository formats, volume handling, and xECM ingestion rules • Collaborate with business stakeholders, PeopleSoft administrators, and repository owners to define migration scope, cutover plans, and post‑migration verification • Document migration artifacts, including mappings, runbooks, and exception‑handling procedures • Partner with xECM Functional Consultants to develop integrated end‑to‑end solutions supporting business and governance requirements

• Design, implement, and optimize technical solutions that support IT Asset Management (ITAM), Software Asset Management (SAM), and Configuration Management Database (CMDB) capabilities. • Partner closely with the Service Asset and Configuration Manager to engineer scalable asset data solutions, automate integrations, and improve the accuracy, reliability, and governance of asset and configuration data within ServiceNow. • Lead the implementation of solutions that enhance asset lifecycle management, strengthen platform integrations, and improve operational efficiency across the enterprise. • Deliver reliable asset management data and solutions to support Oportun's mission to build a better financial future through responsible technology management and operational excellence.

• Lead end-to-end migration of enterprise data platforms from AWS to Google Cloud Platform • Design migration strategies for AWS Redshift, Glue, S3, DynamoDB, Data Lakes, Data Warehouses, and ETL pipelines into GCP-native services • Modernize existing AWS data architectures using Google Cloud best practices • Assess existing AWS environments and recommend optimized GCP solutions • Ensure seamless migration with minimal business disruption • Design scalable batch and streaming data pipelines using Google Dataflow (Apache Beam) • Develop event-driven architectures using Google Pub/Sub • Build enterprise analytical solutions using BigQuery, including streaming inserts and performance optimization • Develop and orchestrate workflows using Cloud Composer (Apache Airflow) • Manage enterprise-scale storage using Google Cloud Storage (GCS) • Implement cloud-native data engineering solutions following Google Cloud best practices • Design, develop, and optimize ETL/ELT pipelines using AWS Glue and AWS Glue DataBrew • Work extensively with Amazon Redshift, Amazon S3, and DynamoDB • Develop scalable ETL workflows using Python, PySpark, and SQL • Build and maintain Data Lakehouse architectures supporting enterprise analytics • Optimize data ingestion, transformation, and loading processes across hybrid cloud environments • Design modern Data Lakehouse, Data Warehouse, and Data Lake architectures • Develop dimensional data models, star schemas, and optimized analytical datasets • Build transformation pipelines using DBT (Data Build Tool) • Write and optimize complex SQL queries for high-performance analytics • Ensure data quality, governance, metadata management, and performance optimization • Lead migration of enterprise dashboards from Qlik Sense to Looker • Translate business reporting requirements into scalable semantic models • Optimize reporting performance using BigQuery and LookML best practices • Collaborate with business stakeholders to modernize enterprise reporting platforms • Lead architecture design sessions and cloud migration workshops • Mentor Data Engineers and establish engineering best practices • Conduct architecture, code, and design reviews • Collaborate with business, DevOps, QA, and Analytics teams • Coordinate effectively with onsite and offshore delivery teams • Implement enterprise security standards across AWS and GCP • Define IAM, encryption, auditing, and monitoring strategies • Ensure compliance with governance and regulatory standards • Establish data quality frameworks and operational monitoring • Gather business requirements and define cloud migration roadmaps • Estimate project efforts and prepare technical solution documents • Manage project timelines, risks, dependencies, and stakeholder communications • Present technical architecture and migration strategies to leadership and clients

Role Description CTG is seeking an experienced Enterprise Data Architect to assess, design, and optimize enterprise data architecture across on-premises and hybrid environments. This role will focus on data modeling, integration, ETL/ELT architecture, metadata management, and data governance while partnering with cross-functional teams to improve enterprise data quality, scalability, and accessibility. Location: Remote or Dallas, TX (preferred) Duration: 2 months Duties: - Design and evaluate enterprise data architecture and integration solutions. - Analyze SQL and NoSQL database schemas and recommend improvements. - Develop conceptual, logical, and physical data models. - Design ETL/ELT processes and enterprise data pipelines. - Create data mapping and transformation specifications. - Assess and improve data quality through profiling and validation. - Document data lineage, source-of-truth, and governance standards. - Support API integrations using REST, SOAP, and event-driven architectures. - Implement metadata management and data cataloging best practices. - Analyze edge application data models and enterprise integration requirements. - Collaborate with business and technical teams to establish enterprise data standards. Qualifications - SQL and NoSQL database schema analysis - Enterprise data architecture (on-premises and hybrid environments) - Conceptual, logical, and physical data modeling - ETL/ELT design and data pipeline development - Data transformation and mapping frameworks - REST, SOAP, and event stream integration - Data profiling and data quality assessment tools - Data lineage and source-of-truth tracking - Data cataloging and metadata management tools - Experience with edge application data models - Strong analytical, communication, and documentation skills Requirements - 8+ years of enterprise data architecture or data engineering experience. - Proven experience designing enterprise data models and integration architectures. - Experience implementing data governance, metadata management, and data quality initiatives. - Experience working within large enterprise environments. - Ability to communicate effectively with technical and business stakeholders. Education - Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related discipline. - Equivalent professional experience will also be considered. - Excellent verbal and written English communication skills and the ability to interact professionally with a diverse group are required. To Apply To be considered, please apply directly to this requisition using the link provided. Kindly forward this to any other interested parties. Thank you! Salary The expected base salary for this position ranges from $50.00 to $55.00/hour. Salary offers are based on a wide range of factors including relevant skills, training, experience, education, market factors, and where applicable, licensure or certifications obtained. In addition to salary, a competitive benefit package is also offered.