Guidehouse
Data Infrastructure Engineer
Vaga remota de Data Engineering com fit claro de localização do candidato.
Publicada2 de jul. de 2026
Países elegíveis1 país aceito
Sinal de senioridadeSenior
Modelo de trabalhoRemoto
Locais aceitos para candidatos
Estados Unidos
Resumo da vaga
Data Infrastructure Engineer
Requisitos e responsabilidades
Conteúdo da vaga extraído em seções para revisão mais rápida.
What You Will Do:
- 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.
What You Will Do:
- 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.
What You Will Do:
- 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.
What You Will Do:
- 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.
What You Will Do:
- 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:
- 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.
- Bachelor’s 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 implementing data ingestion and ETL/ELT workflows, including data modeling and transformation best practices.
- Hands-on experience 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).
- Experience with metadata management and governance: cataloging, lineage, ownership, access controls, classification and policy enforcement.
- Experience implementing automated AWS provisioning using IaC and operating across multiple environments.
- Experience building or operating CI/CD pipelines for data workflows (testing, packaging, deployment automation, environment promotion).
- Solid security fundamentals: IAM/least privilege, encryption, secrets management, secure SDLC practices.
What Would Be Nice To Have:
- Hands-on experience with Databricks
- 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
- 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
Details
- 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
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
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