• Define the end-to-end data roadmap for multilingual and multimodal AI systems, including text, speech, translation, interpretation, low-resource languages, and agentic AI workflows. • Design and build dataset curation pipelines for training, post-training, and evaluation, including cleaning, deduplication, filtering, PII redaction, quality scoring, sampling, balancing, and versioning. • Create annotation schemas, labeling guidelines, QA rubrics, golden datasets, and reviewer workflows for multilingual, speech, translation, and agentic AI data. • Build evaluation datasets and benchmarks, analyze model failure modes, and translate performance gaps into targeted data improvements. • Support post-training data workflows such as SFT, instruction tuning, preference data, RLHF/DPO-style data, reward model data, and synthetic data generation. • Use modern annotation tools and AWS-based data infrastructure to scale secure, traceable, and compliant AI data workflows.

Role Description itD is seeking a Data Engineer IV – Customer Experience & AI Enablement to build scalable data infrastructure, self-service analytics capabilities, and AI-enabled data solutions that support global customer experience and post-sales operations. The ideal candidate will bring deep experience in data engineering, large-scale ETL/ELT pipeline development, workflow orchestration, and analytics enablement, with a track record of delivering reliable data platforms, interactive dashboards, and automation solutions that accelerate business insights and operational efficiency. This is a US-Remote opportunity, with candidates in the PST time zone preferred. Duration: 12 months. Please note that we are only considering direct W2 candidates at this time, as we are unable to offer sponsorship. Responsibilities - Design, develop, integrate, and maintain scalable batch and streaming data pipelines that support customer experience, customer support, survey, and digital support analytics use cases. - Build and optimize production-grade ETL/ELT workflows, data models, and data warehouse architectures to enable efficient, reliable, and scalable analytics. - Develop and maintain workflow orchestration processes for pipeline scheduling, dependency management, monitoring, and operational reliability. - Create interactive self-service dashboards and data visualizations that provide stakeholders with visibility into customer experience trends, operational metrics, and key performance indicators. - Implement data quality, validation, monitoring, alerting, governance, and lineage practices to ensure the accuracy, reliability, and usability of enterprise data assets. - Enable AI and machine learning analytics by developing curated datasets, feature pipelines, model-ready data assets, and AI-assisted analytical workflows. - Leverage large language models and generative AI capabilities to automate data workflows, accelerate insight generation, and reduce manual operational effort. - Partner with analysts, data scientists, engineering teams, customer support, and operations stakeholders to translate data requirements into scalable technical solutions. - Optimize complex SQL queries, data pipelines, storage utilization, and large-scale data processing workflows to improve performance and efficiency. - Champion data literacy and AI enablement through technical documentation, training, best-practice development, and knowledge sharing across cross-functional teams. Internal Responsibilities - Attend regular internal practice community meetings. - Collaborate with your itD practice team on industry thought leadership. - Complete client case studies and learning material, including blogs and media material. - Build out material to contribute to the Digital Transformation practice. - Attend internal itD networking events, both in person and virtual. - Work with leadership on career fast-track opportunities. Qualifications - 6+ years of experience in data engineering, quantitative analytics, operational analytics, or related technical data roles. - Strong proficiency in SQL, including complex queries, query optimization, performance tuning, and window functions. - Strong Python programming experience for data engineering, automation, and large-scale data processing. - Demonstrated experience designing and building production-grade ETL/ELT pipelines and scalable data integration workflows. - Experience with workflow orchestration tools such as Apache Airflow or equivalent data pipeline orchestration technologies. - Experience with large-scale data processing and data warehousing technologies such as Apache Spark, Hive, Presto, Snowflake, or BigQuery. - Hands-on experience building self-service dashboards and data visualizations using Tableau, Looker, or equivalent business intelligence platforms. - Experience developing data models and applying dimensional modeling concepts, including star and snowflake schemas. - Demonstrated experience implementing data quality frameworks, validation processes, monitoring, alerting, and data governance standards. - Experience manipulating large datasets to generate actionable insights and deliver scalable data solutions. - Ability to independently manage multiple technical projects, navigate ambiguity, and deliver data solutions in a fast-paced environment. - Experience communicating complex technical and data concepts to both technical and non-technical stakeholders. - Bachelor's degree in Computer Science or a related technical field. Preferred Qualifications and Skills - Hands-on experience with Generative AI technologies, large language models, or AI-enabled analytics and automation solutions. - Experience with prompt engineering, retrieval-augmented generation architectures, LLM APIs, or AI agent workflows. - Experience building feature pipelines, curated datasets, or model-ready data assets supporting machine learning and AI use cases. - Experience integrating AI or machine learning outputs into dashboards, reporting tools, or operational workflows. - Experience with streaming data technologies such as Kafka or Spark Streaming. - Familiarity with Git, CI/CD practices for data pipelines, and infrastructure-as-code methodologies. - Knowledge of metadata management, data cataloging, and data lineage technologies. - Experience with customer experience, customer support, contact center, or post-sales operations data and metrics. - Experience working with customer support or CRM platforms such as Salesforce. - Experience with digital analytics platforms such as Google Analytics or Adobe Analytics. - Experience using Python or Bash scripting to automate workflows and build internal data tooling. - Familiarity with Agile development methodologies. - Experience working in fast-paced technology, startup, consumer electronics, or high-volume consumer product environments. - Prior contingent workforce or contractor experience supporting large-scale technology organizations. Education - Bachelor's degree in Computer Science or a related technical field required. Benefits - Comprehensive medical benefits. - 401k plan. - Paid holidays. - Networking & career learning and development programs. Company Description About itD: We are part of a new generation of consulting and software development company that blends diversity, innovation, and integrity with real business results. Our structure rejects any strong hierarchy, empowering us to deliver excellent results. We are a woman- and minority-led firm. Every day, we challenge ourselves to be considerate, fair and to re-think what great outcomes mean for our customers. The itD Digital Experience: Joining us means you’ll be part of our global community, you have a say about your own career journey, and you’ll get a chance to give back to causes that matter. You will experience working with Fortune 500 companies and high-performance teams across numerous industries.

• Improve learning data reporting and dashboards in Cornerstone • Integrate Cornerstone + Workday data using existing processes • Conduct user research and usability testing • Create wireframes, prototypes, and user flows • Design accessible, user‑friendly reporting interfaces • Collaborate with L&D, HR, product, and technical teams • Use data insights to optimize reporting and user experience

Role Description Plans, develops, organizes and directs daily operations of the Oncology Data Center in order to meet the goals and objectives of the oncology program. Responsible to ensure that oncology program data is compiled, analyzed and recorded in order to maintain certification by the American College of Surgeons and JCAHO. Qualifications - Certified Tumor Registrar (CTR) or obtain within 12 months of hire date. - Oncology Data Specialist (ODS) credential and/or (formerly known as) Certified Tumor Registrar (CTR) credential from the National Cancer Registrars Association (NCRA) - Excellent written and oral communication skills. - Knowledge of Medical terminology and anatomy. - Knowledge of computers. Requirements - CTR Certification (Preferred) Benefits - Work Hours: 7a-3:30p - Weekend Requirements: No