• Collaborate with Product Managers, Business Analysts, DevOps teams, Engineering teams, PMO. • Deliver scalable enterprise cloud solutions. • Provide architectural options and technical recommendations. • Conduct cost-benefit analysis and risk assessments. • Lead the modernization of data platforms, ETL pipelines, and analytics ecosystems.

• Buscamos un Data Engineer con experiencia en el diseño, construcción y optimización de soluciones de datos escalables • Será responsable de habilitar la integración, procesamiento y disponibilidad de información para iniciativas analíticas, de inteligencia de negocios y ciencia de datos • Colaborar estrechamente con equipos multidisciplinarios y áreas de negocio.

• Collaborate with Data Science, Product Managers and Software Engineers to build robust ETL pipelines that enable the Product Support team to deliver compelling user-facing features • Contribute to architecture decisions, observability tooling, and data quality initiatives that keep our platform robust and maintainable. • Contribute to a scalable internal framework for managing prompt engineering pipelines and other AI workflows. • Enforce and elevate engineering best practices across the AI/ML org, including code quality, testing, and documentation.

Role Description CTG is seeking to fill a Data Engineer – AI & Analytics position for our client. Join a high-impact team helping organizations modernize their data ecosystems to power next-generation AI, machine learning, and analytics solutions. This role is ideal for an experienced Data Engineer who thrives on designing scalable data platforms, building modern data pipelines, and transforming complex data into trusted, AI-ready assets. Location: Remote Duration: 5 months Duties: - Assess customer data environments to evaluate data quality, structure, lineage, and AI/ML readiness. - Design, build, and optimize scalable ETL/ELT pipelines across APIs, relational databases, cloud storage, files, and streaming platforms. - Develop cloud-native data infrastructure supporting enterprise AI, analytics, and machine learning initiatives. - Build high-performance batch and real-time data processing pipelines. - Create reusable, production-ready data assets for analytics, business intelligence, and machine learning teams. - Implement best practices for data governance, security, privacy, metadata management, and regulatory compliance. - Optimize data models, storage formats, and pipeline performance for large-scale processing. - Develop and maintain technical documentation, architecture diagrams, and operational procedures. - Collaborate with data scientists, software engineers, analysts, and business stakeholders to deliver scalable data solutions. - Troubleshoot and resolve complex data integration and performance challenges across modern and legacy environments. Qualifications - Advanced proficiency in Python and SQL for enterprise data engineering. - Experience with PySpark or comparable distributed processing frameworks. - Hands-on experience with Databricks, Apache Spark, or similar cloud data platforms. - Experience using Apache Airflow or equivalent workflow orchestration tools. - Strong knowledge of Parquet, Delta Lake, and modern analytical storage formats. - Experience building streaming solutions using Kafka or equivalent messaging platforms. - Proficiency with Docker, Git, CI/CD pipelines, and DevOps practices. - Strong understanding of cloud data architectures, API development, and distributed systems. - Knowledge of data modeling, performance tuning, and scalable data architecture design. - Familiarity with Master Data Management (MDM), data governance, data lineage, PII compliance, and responsible AI data practices. - Exposure to analytics libraries, statistical computing frameworks, and Natural Language Processing (NLP) technologies is a plus. - Excellent analytical, troubleshooting, and collaboration skills. Requirements - 5+ years of experience in data engineering, cloud data platforms, or big data development. - Demonstrated success designing enterprise-scale data platforms supporting AI, analytics, or machine learning workloads. - Experience developing robust ETL/ELT pipelines across structured, semi-structured, and streaming data sources. - Strong background in application development, API development, debugging, and performance optimization. - Experience working with modern cloud technologies and distributed computing environments. - Ability to translate complex business and technical requirements into scalable data architecture solutions. Education - Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, or a related technical 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. Benefits - The expected base salary for this position ranges from $70.00 to $75.00/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. 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!