Overview CTG is seeking highly skilled and motivated Data Engineers to join our team. This role will provide capacity coverage while SMEs attend Epic training and eliminate risk in analytics engineering/modeling transition from vendor dependency. Role Breakdown (Capability Pool) - 2x Pipeline / Integration Engineers - 2x Machine Learning Engineering / Data Modeling Specialists - 1x Production-Support-Oriented Data Engineer Core Responsibilities - Build and maintain Databricks-based data pipelines - Develop Spark/PySpark transformations - Support GitHub Enterprise workflows - Implement CI/CD (Azure DevOps, Jenkins exposure preferred) - Build consumable data models for analytics users - Respond to production alerts and stabilize pipelines - Reduce dependency on vendor-led analytics modeling Required Skills - Databricks (required) - Spark / PySpark - SQL (advanced) - CI/CD concepts (Azure DevOps or Jenkins) - Data modeling/ machine learning / analytics engineering experience (for modeling roles) Excellent verbal and written English communication skills and the ability to interact professionally with a diverse group are required. CTG does not accept unsolicited resumes from headhunters, recruitment agencies, or fee based recruitment services for this role. To Apply: To be considered, please apply directly to this requisition using the link provided. For additional information, please contact Dallas Bell at Dallas.Bell@ctg.com. Kindly forward this to any other interested parties. Thank you! The expected base salary for this position ranges from $120,000 to $135,000. 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. About CTG CTG, a Cegeka company, is at the forefront of digital transformation, providing IT and business solutions that accelerate project momentum and deliver desired value. Over nearly 60 years, we have earned a reputation as a faster and more reliable, results-driven partner. Our vision is to be an indispensable partner to our clients and the preferred career destination for digital and technology experts. CTG leverages the expertise of over 9,000 team members in 19 countries to provide innovative solutions. Together, we operate across the Americas, Europe, and India, working in close cooperation with over 3,000 clients in many of today's highest-growth industries. For more information, visit www.ctg.com. Our culture is a direct result of the people who work at CTG, the values we hold, and the actions we take. In other words, our people define our culture. It's a living, breathing thing that is renewed every day through the ways we engage with each other, our clients, and our communities. Part of our mission is to cultivate a workplace that attracts and develops the best people. CTG will consider for employment all qualified applicants including those with criminal histories in a manner consistent with the requirements of all applicable local, state, and federal laws. CTG is an Equal Opportunity Employer. CTG will assure equal opportunity and consideration to all applicants and employees in recruitment, selection, placement, training, benefits, compensation, promotion, transfer, and release of individuals without regard to race, creed, religion, color, national origin, sex, sexual orientation, gender identity and gender expression, age, disability, marital or veteran status, citizenship status, or any other discriminatory factors as required by law. CTG is fully committed to promoting employment opportunities for members of protected classes.

CTG is seeking to fill an Enterprise Master Data Management (MDM) Architect position for our client. Location: RemoteDuration: 6 months with possibility for extension Duties: - Conduct a comprehensive assessment of the organization’s current data architecture and enterprise master data environment. - Analyze data structures, integrations, and workflows across multiple enterprise platforms to identify inconsistencies, redundancies, and governance gaps. - Identify data quality, duplication, governance, and integration issues across enterprise systems and develop remediation strategies. - Design and recommend scalable Master Data Management (MDM) architectural improvements to support standardized and trusted enterprise data. - Work hands-on with technical teams to clean, standardize, and rationalize enterprise data sets. - Develop and document enterprise data governance frameworks, policies, standards, and best practices. - Define and optimize data integration and synchronization processes between enterprise systems. - Partner with business leaders, data owners, and IT stakeholders to align data management strategies with business objectives. - Provide architectural guidance and subject matter expertise to support long-term enterprise data governance and quality initiatives. - Document data architecture findings, improvement roadmaps, and recommended governance practices. Skills: - Strong expertise in Enterprise Master Data Management (MDM) architecture and data governance frameworks. - Hands-on experience analyzing enterprise data models, system integrations, and complex data flows. - Deep understanding of data quality management, data lifecycle management, and enterprise data governance practices. - Strong knowledge of data modeling, metadata management, and data integration architectures. - Experience evaluating and improving enterprise data ecosystems to reduce duplication and increase data reliability. - Ability to translate complex data architecture concepts into practical solutions for technical and business stakeholders. - Strong analytical, documentation, and communication skills. - Ability to collaborate effectively with cross-functional teams across business and IT. Experience: - Proven experience as an Enterprise Data Architect, MDM Architect, or Data Governance Architect in complex enterprise environments. - Demonstrated success identifying and resolving data quality, duplication, and master data management challenges. - Experience conducting enterprise data landscape assessments and implementing architectural improvements. - Hands-on experience working with enterprise platforms including: - SAP - Blue Yonder - Alation - ServiceNow - Syndigo - Workday - Experience with data cataloging tools, metadata management platforms, and enterprise integration environments is highly preferred. - Experience working with cross-functional business and technical teams to implement scalable enterprise data solutions. Education: - Bachelor’s degree in Computer Science, Information Systems, Data Management, or a related field, or equivalent experience. - Master’s degree or relevant data architecture certifications preferred. Excellent verbal and written English communication skills and the ability to interact professionally with a diverse group are required. CTG does not accept unsolicited resumes from headhunters, recruitment agencies, or fee based recruitment services for this role. To Apply:To be considered, please apply directly to this requisition using the link provided. For additional information, please contact Tana Stilloe at Tana.Stilloe@ctg.com. Kindly forward this to any other interested parties. Thank you! The expected base salary for this position ranges from $76.00 to $85.00/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. About CTG CTG, a Cegeka company, is at the forefront of digital transformation, providing IT and business solutions that accelerate project momentum and deliver desired value. Over nearly 60 years, we have earned a reputation as a faster and more reliable, results-driven partner. Our vision is to be an indispensable partner to our clients and the preferred career destination for digital and technology experts. CTG leverages the expertise of over 9,000 team members in 19 countries to provide innovative solutions. Together, we operate across the Americas, Europe, and India, working in close cooperation with over 3,000 clients in many of today's highest-growth industries. For more information, visit www.ctg.com. Our culture is a direct result of the people who work at CTG, the values we hold, and the actions we take. In other words, our people define our culture. It's a living, breathing thing that is renewed every day through the ways we engage with each other, our clients, and our communities. Part of our mission is to cultivate a workplace that attracts and develops the best people. CTG will consider for employment all qualified applicants including those with criminal histories in a manner consistent with the requirements of all applicable local, state, and federal laws. CTG is an Equal Opportunity Employer. CTG will assure equal opportunity and consideration to all applicants and employees in recruitment, selection, placement, training, benefits, compensation, promotion, transfer, and release of individuals without regard to race, creed, religion, color, national origin, sex, sexual orientation, gender identity and gender expression, age, disability, marital or veteran status, citizenship status, or any other discriminatory factors as required by law. CTG is fully committed to promoting employment opportunities for members of protected classes.

Design and scale data systems and pipelines, develop strategies for web data capture, and optimize ETL/ELT processes while ensuring high data quality and collaborating with cross-functional teams to achieve business objectives.

Role Description Saaf AI is building the future of mortgage lending by combining cutting-edge AI with robust data infrastructure. As part of a top-10 private lender processing billions in loan volume, backed by leading asset managers and funds, we are growing fast — and data and AI are at the center of everything we build. We don’t just experiment with AI — we integrate it deeply into how we operate. Our systems rely on scalable data pipelines, structured data models, and real-time workflows that power underwriting, document processing, and borrower interactions. AI is embedded across these layers, from data extraction and validation to intelligent automation. If you’re excited about building high-quality data systems in an AI-native environment — where data pipelines, automation, and intelligent workflows come together — you’ll fit right in. Key Responsibilities - Data Pipeline Development - Design, implement, and maintain ETL/ELT pipelines for structured and unstructured datasets from internal and external sources. - Leverage AI-assisted development tools to accelerate pipeline authoring, generate transformation logic, and automate boilerplate code. - Data Warehousing & Modeling - Build and optimize data warehouses and marts (Snowflake, BigQuery, or similar) for analytics, reporting, and product use cases. - Design, implement, and maintain conceptual, logical, and physical data models to ensure scalable, consistent, and high-quality datasets for downstream analytics and applications. - Integration & Ingestion - Ingest data from APIs, SaaS platforms (CRM, financial data APIs), and internal systems into the core data platform. - Build and maintain reliable connectors and ingestion frameworks that handle schema evolution, rate limits, and error recovery. - Data Quality & Governance - Implement validation, schema management, and robust documentation to ensure data accuracy and compliance. - Use AI tools to support data profiling, anomaly detection, and automated documentation of data lineage and transformations. - AI-Integrated Data Engineering - Use AI-assisted tools (code generation, intelligent autocomplete, automated testing) as a regular part of your data engineering workflow. - Evaluate and integrate emerging AI tools and practices into the team's data development process. - Build and support agentic workflows and multi-step automated processes that act on data in real time, including AI-powered data validation and enrichment. - Apply AI-assisted analysis to debugging pipeline failures, optimizing query performance, and identifying data quality issues. - Performance & Reliability - Monitor and fine-tune pipeline and warehouse performance for scalability and cost efficiency. - Set up logging, monitoring, and alerting for data jobs to ensure reliability and fast incident response. - Security & Compliance - Apply data security and privacy controls aligned with financial regulatory requirements, ensuring full traceability of every transformation. - Foster a security-first mindset across all data operations. - Analytics Enablement - Provide clean, consistent datasets for analysts, product managers, and operational teams to support fast, data-driven decisions. - Collaborate closely with product managers, data scientists, and full stack engineers to align data models with business needs. Qualifications - 5+ years in a data engineering or similar backend data-focused role. - Strong SQL and Python development skills for data transformation and automation. - Experience with modern ETL/ELT frameworks such as dbt. - Proficiency with cloud platforms (AWS preferred) and serverless data services. - Strong experience with data warehouse technologies (Snowflake preferred). - Skilled in API integrations and ingestion from third-party systems. - Proficient in data modeling (Kimball/Star schema, Data Vault). - Demonstrated, regular use of AI-powered development tools (e.g., Cursor, GitHub Copilot, Claude Code, or similar) to accelerate data pipeline development, debugging, or documentation. - Proven track record of delivering production-grade data pipelines at scale. - Experience implementing CI/CD practices for data workflows. - Experience collaborating closely with product managers, data scientists, and full stack engineers. - Startup mindset: hands-on, resourceful, and comfortable operating in a fast-paced environment. Preferred - Experience building agentic workflows and orchestrating multi-step automated processes that act on data in real time. - Familiarity with data engineering patterns and infrastructure required for AI-powered tools and automation platforms. - Experience working with financial datasets and APIs in a high-compliance environment. - Understanding of data privacy regulations such as GDPR and CCPA. - Experience with prompt engineering for code generation, data transformation logic, or building AI-powered data workflows. Benefits - Competitive salary - Unlimited PTO - Remote-first with flexible hours - Up to $2,000/year professional development budget - Home office setup stipend