Role Description itD is seeking a Data Engineer IV to design, build, and optimize scalable data infrastructure that supports AI infrastructure and inference initiatives for a high-performing engineering organization. The ideal candidate will bring deep expertise in data engineering, AWS, large-scale ETL development, and analytics, with a proven track record of: - Building end-to-end data pipelines - Transforming raw data into production-ready datasets - Delivering reliable enterprise data solutions that improve operational efficiency and system reliability Location: Remote (Candidates must be located within the Pacific Time Zone.) Pay Rate: Depending on experience. Duration: 6 months We provide comprehensive medical benefits, a 401(k) plan, paid holidays, and more. Please note that we are only considering direct W2 candidates at this time, as we are unable to offer sponsorship. Responsibilities - Design, develop, and maintain end-to-end data pipelines and scalable data architectures using AWS technologies. - Build and optimize ETL processes that transform raw data into structured, analytics-ready datasets. - Design, implement, automate, and support enterprise-scale data management systems that meet business and engineering requirements. - Partner with AI infrastructure engineers, data architects, and cross-functional stakeholders to improve data reliability, scalability, and operational efficiency. - Develop high-performance data processing solutions, prototypes, and proof-of-concept implementations to support infrastructure initiatives. - Manage data engineering projects through the full development lifecycle, from requirements gathering to deployment and ongoing optimization. - Identify opportunities to improve existing data processes, enhance system performance, and implement engineering best practices. 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 (blogs, media material). - Build out material to contribute to the Digital Transformation practice. - Attend internal itD networking events (in person and virtual). - Work with leadership on career fast-track opportunities. Qualifications - Bachelor's degree in Computer Science, Computer Engineering, Data Engineering, or a related technical field. - 8+ years of experience in data engineering or a related technical discipline. - Experience designing and building end-to-end data pipelines from scratch using AWS. - Experience developing and maintaining large-scale ETL processes and enterprise data solutions. - Experience transforming raw data into structured, analytics-ready data models and tables. - Strong analytical skills with experience solving complex data engineering challenges. - Experience collaborating with data architects, software engineers, and cross-functional technical teams. - Excellent written, verbal, and presentation communication skills. Preferred Qualifications and Skills - Experience supporting AI infrastructure, machine learning platforms, or inference systems. - Infrastructure engineering or platform engineering experience. - Previous experience working in large-scale technology organizations. - Previous experience supporting Meta or similar enterprise environments. - Process improvement certifications such as Six Sigma, CBPP, BPM, ISO 20000, ITIL, or CMMI. Education - Bachelor's degree in Computer Science, Computer Engineering, Data Engineering, or a related technical field required. 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. This permeates down to how we approach every interaction, on every project, for every client. You’ll thrive here if you are a dynamic self-starter, a difference-maker or someone who wants to deliver great results, without constraints. 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. itD offers our employees excellent benefits such as medical, dental, vision, life insurance, paid holidays, 401K + matching, networking & career learning and development programs. We are growing and we want to see you grow! Visit https://itdtech.com/careers to learn more about what working at itD can mean for you. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or protected veteran status, or any other legally protected basis, in accordance with applicable law. itD is committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or to perform the essential functions of a position, please contact us at recruiting@itdtech.com and let us know the nature of your request and your contact information. Dynamic environment in a culture of respect, empowerment and recognition for a job well done, apply today!

• Design, build, and maintain scalable data pipelines across internal databases, vendor systems, and our data warehouse • Support both batch and event-driven or CDC-based data workflows • Improve pipeline reliability, observability, and performance • Troubleshoot issues in production and proactively solve data quality or system problems • Build and maintain data warehouse schemas and transformation layers to support analytics and operational use cases • Communicate clearly about implementation choices, tradeoffs, and technical constraints • Identify opportunities to improve data workflows through better tooling, automation, and engineering practices • Help shape scalable patterns for how data is ingested, transformed, stored, and accessed

• Own data pipeline design and implementation; consolidate 250+ transactional tables into ~10 analytic tables; move from weekly full-refresh to daily/near-real-time incremental loads via CDC (e.g., AWS DMS). Build and own the centralized analytics layer. • Establish unified data definitions, metrics, KPIs, and benchmarks across the organization. Deliver a Master Data Management (MDM) framework with unified definitions and governance standards. • Drive migration to the centralized layer while deprecating direct raw table access. • Partner with internal departments to drive self-service analytics and build aggregations/data marts for benchmarking and experimentation. • Conduct exploratory and statistical analysis for data validation, and implement data observability/monitoring. • Partner with the Applied AI Engineer to design AI-ready data models (including retrieval- and embedding-ready structures to ground RAG and LLM applications). Expand the data lake to ingest third-party sources (e.g., HubSpot, Jira, Zendesk).

Role Description - Monitor and support daily ELT pipelines and reporting processes. - Design, document, and maintain data warehouse models as source systems evolve. - Develop and maintain semantic-layer and business intelligence data models. - Support month-end reporting and recurring business processes. - Improve and prepare data assets for AI-enabled workflows and automation initiatives. - Design data transformations that enhance data quality, consistency, accessibility, and usability. - Troubleshoot data issues and support analytics requests across the organization. - Serve as the primary technical resource for analytics infrastructure and reporting systems. - Prepare internal metrics, analytics, and leadership reporting. - Collaborate with stakeholders on data-driven initiatives and continuous improvements. Qualifications - 4+ years of experience in analytics engineering, data engineering, business intelligence, analytics, or related fields. - Strong understanding of data warehousing, dimensional modeling, and semantic-layer concepts. - Experience building and maintaining ELT/ETL pipelines. - Strong SQL and data modeling skills. - Experience working with software engineering workflows and source control. - Strong communication, documentation, and stakeholder management skills. - Hands-on experience with dbt, Amazon Redshift, Amazon QuickSight, AWS, Python, GitHub, Docker, and SQL. - Advanced English. Requirements - Experience with CI/CD workflows. - Knowledge of data governance practices and experience in healthcare, finance, or other regulated industries. Benefits - Great Place To Work certification. - A company with more than 15 years of experience. - Work with world-class clients and long-term projects. - English scholarships for an external institute. - English classes with company teachers. - State-of-the-art tools and resources. - Certifications for your professional growth. - Recreation and leisure activities. - Compliance with the regulations and labor rights of your region.