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About This Role
Job Family:
Technology Consulting Travel Required:
Up to 50% Clearance Required:
Ability to Obtain Public TrustWhat You Will Do:
The API Developer/Data Engineering Managing (Lead) Consultant serves as a trusted advisor and delivery lead for AI and Data engagements. This role owns solution strategy, oversees delivery teams, develops technical solutions, and partners with clients to drive measurable business outcomes.
Key Responsibilities
- Lead the design, development, and deployment of data integration and API solutions within related data platforms.
- Architect and implement end\-to\-end data pipelines, including ingestion, transformation, validation, and delivery of structured and unstructured data.
- Develop and maintain ontology models, data schemas, and relationships to support analytics, search, and operational use cases.
- Integrate data across multiple systems and platforms (e.g., cloud storage, APIs, analytics environments) using scalable and secure patterns.
- Collaborate with cross\-functional teams (data engineering, analytics, product, and security) to ensure seamless system interoperability and data consistency.
- Implement data validation, quality assurance, and governance processes (e.g., completeness checks, schema validation, metadata integrity).
- Support development of AI\-enabled capabilities (e.g., semantic search, entity resolution, analytics) by enabling high\-quality, well\-structured data pipelines.
- Operate within an Agile delivery model, contributing to sprint planning, backlog refinement, user story development, and iterative delivery of technical solutions.
- Translate business and mission needs into technical requirements and scalable integration designs.
- Ensure compliance with security, privacy, and audit requirements, including role\-based access controls, logging, and data protection standards.
- Drive technical design decisions, mentor junior engineers, and act as a technical lead within a matrixed team environment.
What You Will Need:
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field (or equivalent experience).
- Based on our contractual obligations, candidate must be located within the United States and a US Citizen.
- Must be able to OBTAIN and MAINTAIN a Federal or DoD "PUBLIC TRUST" clearance.
- 5\+ years of experience in data engineering, system integration, or platform engineering roles.
- Proficiency in Python, Java/JS, .NET (C\#), RESTful API, XML, and strong SQL skills (including SQL Server) with experience integrating APIs with enterprise applications, databases, and third\-party systems.
- Proficiency in Java/JS, .NET (C\#), RESTful API, XML for data transformation, querying, and API development.
- Proficiency working with various data structure formats (CSV/TXT, JSON, XML, Parquet, etc.).
- Strong hands\-on experience with API development and integration, including:
+ Building and managing data pipelines
+ Ontology/data model development and relationship mapping
+ Integration of data across multiple systems
- Experience working within cloud platforms (particularly GCP) for scalable data transformation, enrichment, and analytics workflows.
- Strong understanding of data modeling, schema alignment, and metadata management across integrated systems.
- Experience implementing data quality, validation, and governance controls.
- Familiarity with cloud security and access controls, including IAM, encryption, and audit logging.
- Proven ability to lead technical workstreams, mentor junior staff, and collaborate across cross\-functional and matrixed teams.
- Preference will be given to candidates located in the DMV.
- Travel may be up to 25\-50% for candidates not located in the DMV.
What Would Be Nice to Have:
- Experience building APIs for and/or working with entity validation/entity resolution solutions.
- Experience with API gateways (Apigee, Kong, Azure API Management, AWS API Gateway).
- Experience with Python and SQL (including SQL Server).
- Previous experience working with federal agencies or government environments, including familiarity with security, compliance, and data governance requirements.
- Previous experience working with LexisNexis (or other similar third\-party data provider) products via API endpoints and integrating data into solution environment(s).
- Experience working in a consulting environment and/or delivering solutions in a matrixed organization.
- Experience supporting training, user enablement, and scaling of technical capabilities across teams or organizations.
- Experience building AI/ML\-enabled data products, particularly those leveraging unstructured data (e.g., NLP, document processing, image\-based analytics).
- Familiarity with ontology\-driven applications, graph\-based data modeling, and relationship analytics.
- Experience implementing role\-based access control (RBAC) and auditability compliance.
- Relevant certifications or equivalent demonstrated expertise.
- Experience with fraud and/or FinCrime data and monitoring systems.
- Hands\-on experience with financial crime compliance technology and data solutions, e.g., Oracle Mantas, Actimize, Fircosoft, LexisNexis Bridger, World\-Check, Dow Jones, Chainalysis, Elliptic, TRM Labs, etc.
The annual salary range for this position is $130,000\.00\-$216,000\.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
- Position may be eligible for a discretionary variable incentive bonus
- Parental Leave and Adoption Assistance
- 401(k) Retirement Plan
- Basic Life \& Supplemental Life
- Health Savings Account, Dental/Vision \& Dependent Care Flexible Spending Accounts
- Short\-Term \& Long\-Term Disability
- Student Loan PayDown
- Tuition Reimbursement, Personal Development \& Learning Opportunities
- Skills Development \& Certifications
- Employee Referral Program
- Corporate Sponsored Events \& Community Outreach
- Emergency Back\-Up Childcare Program
- Mobility Stipend
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 [email protected]. 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 [email protected]. 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 [email protected]. 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.*
Salary Context
This $130K-$216K range is above the 75th percentile for Data Engineer roles in our dataset (median: $150K across 15 roles with salary data).
Role Details
About This Role
Data Engineers build the pipelines that feed AI models. They design ETL workflows, manage data lakes, and ensure training and inference data is clean, timely, and accessible. Without good data engineering, AI projects fail. It's that simple.
The AI era has expanded the data engineer's scope far beyond batch ETL jobs. You're building real-time embedding pipelines for RAG systems, managing vector databases, ensuring training data quality at scale, and building the infrastructure that lets ML teams iterate on data as fast as they iterate on models. Data quality is the biggest predictor of model quality, and you're the person responsible for it.
Across the 3,708 AI roles we're tracking, Data Engineer positions make up 1% of the market. At Guidehouse, this role fits into their broader AI and engineering organization.
Data Engineer demand in AI contexts is strong and growing. Every company building AI needs clean, reliable data pipelines. The shift toward real-time AI applications (chatbots, recommendation engines, agent systems) means data engineering is more critical than ever. Companies are willing to pay premium salaries for data engineers with AI/ML pipeline experience.
What the Work Looks Like
A typical week includes: debugging a data pipeline that's producing stale embeddings for the RAG system, optimizing a Spark job that processes training data, building a data quality monitoring dashboard, meeting with the ML team to understand their next data requirements, and writing dbt models that transform raw event data into ML-ready features. The work is deeply technical and high-impact.
Data Engineer demand in AI contexts is strong and growing. Every company building AI needs clean, reliable data pipelines. The shift toward real-time AI applications (chatbots, recommendation engines, agent systems) means data engineering is more critical than ever. Companies are willing to pay premium salaries for data engineers with AI/ML pipeline experience.
Skills Required
SQL, Python, and distributed systems (Spark, Airflow, dbt) are core. Cloud data platforms (Snowflake, BigQuery, Redshift) are increasingly standard. Many AI-focused roles also want familiarity with vector databases and embedding pipelines. Understanding data modeling, pipeline orchestration, and data quality frameworks covers the essentials.
AI-specific data engineering skills include: building feature stores, managing training data versioning, implementing data lineage tracking, and building real-time embedding pipelines. Experience with streaming systems (Kafka, Flink) is valuable for real-time AI applications. Understanding ML data requirements (balanced datasets, data augmentation, evaluation set construction) makes you much more effective working with ML teams.
Strong postings specify the data stack, mention ML pipeline work, and describe the scale of data you'll be working with. Look for companies that understand the connection between data quality and model quality. Avoid roles that conflate data engineering with data analysis.
Compensation Benchmarks
Data Engineer roles pay a median of $178,800 based on 40 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. Disclosed range: $130K to $216K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Guidehouse AI Hiring
Guidehouse has 6 open AI roles right now. They're hiring across Data Engineer, AI/ML Engineer, AI Software Engineer, Data Scientist. Positions span New York, NY, US, Chicago, IL, US, Washington, DC, US. Compensation range: $124K - $216K.
Location Context
AI roles in New York pay a median of $220,000 across 1,045 tracked positions.
Career Path
Common paths into Data Engineer roles include Backend Engineer, Database Administrator, Analytics Engineer.
From here, career progression typically leads toward Senior Data Engineer, ML Engineer, Data Platform Lead.
Master SQL and Python first. Then learn a distributed processing framework (Spark or its modern alternatives) and a pipeline orchestrator (Airflow, Dagster, Prefect). Build a portfolio project that demonstrates end-to-end pipeline construction: ingest, transform, validate, serve. If you want to specialize in AI data engineering, add vector databases and embedding pipelines to your skill set.
What to Expect in Interviews
Expect SQL deep-dives (query optimization, partitioning strategies, data modeling), Python coding focused on data pipeline patterns, and system design questions about building scalable ETL workflows. Companies with ML teams will ask about feature stores, embedding pipelines, and training data management. Be ready to discuss data quality monitoring, pipeline orchestration, and how you'd handle schema evolution in a production data lake.
When evaluating opportunities: Strong postings specify the data stack, mention ML pipeline work, and describe the scale of data you'll be working with. Look for companies that understand the connection between data quality and model quality. Avoid roles that conflate data engineering with data analysis.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Data Engineer demand in AI contexts is strong and growing. Every company building AI needs clean, reliable data pipelines. The shift toward real-time AI applications (chatbots, recommendation engines, agent systems) means data engineering is more critical than ever. Companies are willing to pay premium salaries for data engineers with AI/ML pipeline experience.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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