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We are seeking aData Infrastructure Engineerto build andoperatethe data platform that powersAI/ML analytics modules. You will design and implement scalabledata ingestion pipelines, robustETL/ELT, and a moderndata lake / delta lake (lakehouse)onAWS.Youllalsoestablishamanaged metadata repositoryand governance layers (catalog, lineage, quality, access controls) and deliverautomated cloud provisioningplusCI/CD for data pipelinesto 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 &OperateData Pipelines (Batch + Streaming)

• Design and implementbatch and streaming ingestionfrom APIs, relational databases, file drops, event streams, and external partners.

• Build andoptimizeETL/ELT pipelinesto produce curated, analytics-ready datasets for reporting and ML consumption.

• Implement incremental processing patterns, change data capture (CDC) approaches whereappropriate, and data contract standards.

Deliver a Modern Lakehouse (Data Lake / Delta Lake)

• Build and manage a scalablelakehouseon AWS object storage (e.g., S3) using open table/file formats and delta/lakehouseconcepts (e.g., ACID tables, schema evolution, time travel patterns).

• Optimizeperformance 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 amanaged metadata repositoryfor dataset cataloging, ownership, glossary/definitions, tagging, and discoverability.

• Enableend-to-end lineage(source 1 transformations 1 consumption) to support auditability and impact analysis.

• Implementgovernance 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

• Implementautomated cloud provisioning in AWSusing Infrastructure as Code (IaC) for consistent environments and secure-by-default baselines.

• Build and enhanceCI/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 includingSOPs, system diagrams, and secure configuration baselines.

• Summarize and present findings and recommendationsboth written and verbalto technical and non-technical stakeholders.

What You Will Need:

• Must be able to OBTAIN and MAINTAIN a Federal or DoD 2PUBLIC TRUST2; candidates must obtain approved adjudication of their PUBLIC TRUST prior to onboarding with Guidehouse. Candidates with an ACTIVE PUBLIC TRUST or SUITABILITY are preferred.

• Bachelors degree in Engineering, IT, Computer Science, or related field (or equivalent experience).

• Minimum of FOUR (4) years experience building production data pipelines and/or data platforms.

• Strong experience implementingdata ingestionandETL/ELTworkflows, including data modeling and transformation best practices.

• Hands-on experience building adata lake / delta lake (lakehouse)on AWS (or equivalent cloud) using object storage and modern table formats/patterns.

• ProficiencyinSQLand one programming language commonly used for data engineering (Python preferred; Scala/Java acceptable).

• Experience withmetadata management and governance: cataloging, lineage, ownership, access controls,classificationand policy enforcement.

• Experience implementingautomated AWS provisioningusingIaCandoperatingacross multiple environments.

• Experience building or operatingCI/CD pipelinesfor data workflows (testing, packaging, deployment automation, environment promotion).

• Solid security fundamentals: IAM/least privilege, encryption,secretsmanagement, secure SDLC practices.

What Would Be Nice To Have:

• Hands-on experience with Databricks

• Hands-on experienceutilizingmodern DevOps practices, including tools likeGit, Terraform, Jenkins, AWSCodePipeline, and Docker.

• ExperienceutilizingAI-assisted coding tools(e.g.,GitHub Copilot, ChatGPT, Cursor, Kiro) to safely accelerate implementation whilemaintainingstrict code quality throughtesting, code reviews, and security practices.

• Knowledge graph and Graph RAGexperience, 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

#LI-DNI

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