• Design and implement robust, scalable data pipelines to meet various business and analytics team needs. • Integrate and process large volumes of data from diverse sources (structured and unstructured). • Contribute to defining and standardizing data engineering best practices and ensure data quality and integrity. • Develop automation solutions for data ingestion, transformation and provisioning routines. • Support business areas with technical solutions aimed at democratizing data (self-service BI, catalogs, data models). • Actively participate in agile ceremonies and collaborate with multidisciplinary teams across data, product and technology. • Document processes, data flows and technical standards to promote reuse and scalability.

• Design and develop data ingestion pipelines from external sources (ETLs, APIs, relational and non-relational databases, files, telemetry sensors, etc.); • Integrate and consolidate data from different sources within the Azure environment, ensuring data quality and consistency; • Implement reference architecture for data processing and storage; • Create and manage data lakes, data warehouses, and data marts within the Azure ecosystem; • Develop and optimize ETL/ELT processes using Microsoft tools such as Azure Data Factory, Databricks, Synapse Analytics, and Azure Functions; • Ensure governance, security, and scalability of data pipelines; • Monitor and optimize data load performance, identify bottlenecks, and propose improvements; • Work closely with data scientists and functional analysts to meet business needs.

Title: Data Infrastructure Engineer Location: US - Remote (Any location) Job Description: Job Family:Data Science& Analysis Travel Required:None Clearance Required:Ability to Obtain Public Trust We are seeking a Data Infrastructure Engineer to build and operate the data platform that powers AI/ML analytics modules. You will design and implement scalable data ingestion pipelines, robust ETL/ELT, and a modern data lake / delta lake (lakehouse) on AWS. You’ll also establish a managed metadata repository and governance layers (catalog, lineage, quality, access controls) and deliver automated cloud provisioning plus CI/CD for data pipelines to enable reliable, repeatable deployments across environments. This role is ideal for an engineer who enjoys platform building, automation, and enabling advanced analytics through trusted, well-governed data. What You Will Do: Build & Operate Data Pipelines (Batch + Streaming) - Design and implement batch and streaming ingestion from APIs, relational databases, file drops, event streams, and external partners. - Build and optimize ETL/ELT pipelines to produce curated, analytics-ready datasets for reporting and ML consumption. - Implement incremental processing patterns, change data capture (CDC) approaches where appropriate, and data contract standards. Deliver a Modern Lakehouse (Data Lake / Delta Lake) - Build and manage a scalable lakehouse on AWS object storage (e.g., S3) using open table/file formats and delta/lakehouse concepts (e.g., ACID tables, schema evolution, time travel patterns). - Optimize performance and cost through partitioning, compaction, lifecycle policies, and efficient compute/storage usage. - Establish environment standards for dev/test/prod and consistent promotion across stages. Metadata, Governance, Lineage & Quality (Trust Layer) - Implement a managed metadata repository for dataset cataloging, ownership, glossary/definitions, tagging, and discoverability. - Enable end-to-end lineage (source → transformations → consumption) to support auditability and impact analysis. - Implement governance controls including policy-based access, data classification, retention, and secure data handling. - Build operational data quality checks (freshness, completeness, validity, anomaly detection) and publish SLAs/SLOs. AWS Automation + CI/CD for Data Pipelines - Implement automated cloud provisioning in AWS using Infrastructure as Code (IaC) for consistent environments and secure-by-default baselines. - Build and enhance CI/CD for data pipelines, including automated tests, validation gates, promotion workflows, and rollback strategies. - Improve observability with metrics/logs/alerts, dashboards, runbooks, and incident response readiness. Cross-Team Collaboration & Documentation - Work closely with engineering, security, networking, and application teams to support mission needs and delivery timelines. - Maintain high-quality engineering documentation including SOPs, system diagrams, and secure configuration baselines. - Summarize and present findings and recommendations—both written and verbal—to technical and non-technical stakeholders. What You Will Need: - Bachelor’s degree in Engineering, IT, Computer Science, or related field (or equivalent experience). - Zero(0) to Two(2) Years of experience. - Experience building production data pipelines and/or data platforms. - Knowledge in implementing data ingestion and ETL/ELT workflows, including data modeling and transformation best practices. - Knowledge in building a data lake / delta lake (lakehouse) on AWS (or equivalent cloud) using object storage and modern table formats/patterns. - Proficiency in SQL and one programming language commonly used for data engineering (Python preferred; Scala/Java acceptable). - Knowledge with metadata management and governance: cataloging, lineage, ownership, access controls, classification and policy enforcement. - Knowledge in implementing automated AWS provisioning using IaC and operating across multiple environments. - Proven experience developing RAG applications - Solid security fundamentals: IAM/least privilege, encryption, secrets management, secure SDLC practices. - Must be able to OBTAIN and MAINTAIN a Federal or DoD "PUBLIC TRUST"; candidates must obtain approved adjudication of their PUBLIC TRUST prior to onboarding with Guidehouse. Candidates with an ACTIVE PUBLIC TRUST or SUITABILITY are preferred. What Would Be Nice To Have: - Hands-on experience with Databricks - Experience in operating CI/CD pipelines for data workflows (testing, packaging, deployment automation, environment promotion). - Hands-on experience utilizing modern DevOps practices, including tools like Git, Terraform, Jenkins, AWS CodePipeline, and Docker. - Experience utilizing AI-assisted coding tools (e.g., GitHub Copilot, ChatGPT, Cursor, Kiro) to safely accelerate implementation while maintaining strict code quality through testing, code reviews, and security practices. - Knowledge graph and Graph RAG experience, including: - Graph modeling and ontology/taxonomy alignment - Entity resolution and relationship extraction - Hybrid retrieval approaches combining graph traversal with semantic/vector search to improve grounding and explainability The annual salary range for this position is $65,000.00-$108,000.00. Compensation decisions depend on a wide range of factors, including but not limited to skill sets, experience and training, security clearances, licensure and certifications, and other business and organizational needs. What We Offer: Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace. Benefits include: - Medical, Rx, Dental & Vision Insurance - Personal and Family Sick Time & Company Paid Holidays - Parental Leave - 401(k) Retirement Plan - Group Term Life and Travel Assistance - Voluntary Life and AD&D Insurance - Health Savings Account, Health Care & Dependent Care Flexible Spending Accounts - Transit and Parking Commuter Benefits - Short-Term & Long-Term Disability - Tuition Reimbursement, Personal Development, Certifications & Learning Opportunities - Employee Referral Program - Corporate Sponsored Events & Community Outreach - Care.com annual membership - Employee Assistance Program - Supplemental Benefits via Corestream (Critical Care, Hospital Indemnity, Accident Insurance, Legal Assistance and ID theft protection, etc.) - Position may be eligible for a discretionary variable incentive bonus About Guidehouse Guidehouse is an Equal Opportunity Employer–Protected Veterans, Individuals with Disabilities or any other basis protected by law, ordinance, or regulation. Guidehouse will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of applicable law or ordinance including the Fair Chance Ordinance of Los Angeles and San Francisco. If you have visited our website for information about employment opportunities, or to apply for a position, and you require an accommodation, please contact Guidehouse Recruiting at 1-571-633-1711 or via email at RecruitingAccommodation@guidehouse.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodation. All communication regarding recruitment for a Guidehouse position will be sent from Guidehouse email domains including @guidehouse.com or guidehouse@myworkday.com. Correspondence received by an applicant from any other domain should be considered unauthorized and will not be honored by Guidehouse. Note that Guidehouse will never charge a fee or require a money transfer at any stage of the recruitment process and does not collect fees from educational institutions for participation in a recruitment event. Never provide your banking information to a third party purporting to need that information to proceed in the hiring process. If any person or organization demands money related to a job opportunity with Guidehouse, please report the matter to Guidehouse’s Ethics Hotline. If you want to check the validity of correspondence you have received, please contact recruiting@guidehouse.com. Guidehouse is not responsible for losses incurred (monetary or otherwise) from an applicant’s dealings with unauthorized third parties. Guidehouse does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Guidehouse and Guidehouse will not be obligated to pay a placement fee.

• Prepare, organize and make data available for analytical, operational and governance use. • Design, develop and maintain scalable data pipelines for extraction, integration, consolidation, transformation and processing of data from multiple sources. • Create interfaces, flows and mechanisms that ensure secure, efficient and reliable access to information. • Implement and administer solutions using Informatica Cloud Data Governance and Catalog (CDGC). • Work together with business and technology teams to define and implement data governance policies, standards and best practices. • Integrate governance and data catalog solutions with enterprise platforms and cloud environments. • Support initiatives related to Data Quality, Master Data Management (MDM) and Reference Data Management (RDM). • Ensure that data assets are reliable, traceable, accessible and compliant with organizational standards.