Hashi Vault Data Jobs

2 jobs found

1d ago

Senior Consultant, Strategy, Growth, and Transformation, Identity & Gen AI Engineer

Deloitte Baltimore, MD

Baltimore, MD

1d ago

$105k - $208k/yr Full time Senior Artificial Intelligence Cedar

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Job Description

Deloitte offers an onsite Senior Consultant role in Baltimore, MD, focused on building secure GenAI solutions with identity, access, and governance controls. You will work on authentication, authorization, and policy enforcement for AI agents and data access across enterprise and cloud environments. The position provides a competitive salary range of USD 105,400 - 207,800 per year and a discretionary annual incentive program, with opportunities to collaborate closely with IAM, security architecture, and data teams to embed identity controls throughout GenAI delivery.

Location: Baltimore, MD (onsite)

Salary: USD 105,400 - 207,800 per year

Responsibilities

Build and integrate generative AI solutions, including LLM applications, retrieval-augmented generation, and AI agents, with secure access to data and downstream systems.
Engineer authentication, authorization, and identity controls for AI agents, service accounts, and other non-human identities operating across enterprise and cloud environments.
Develop guardrails for agentic workflows, including scoped permissions, least-privilege access, credential and secrets management, and runtime policy enforcement.
Implement logging, monitoring, and governance that provide traceability and accountability for AI system actions.
Collaborate with IAM, security architecture, and data teams to embed identity controls into GenAI solution delivery and operations.
Create and maintain reference architectures, reusable patterns, and technical documentation for building and securing AI systems.

Requirements

Bachelor's degree in Cybersecurity, Computer Science, Information Systems, Engineering, or a similar technical field
Ability to work onsite up to 5 days a week
3+ years of software engineering experience with Python or a comparable language
1+ year of hands-on experience building, integrating, or deploying generative AI solutions such as large language model applications, retrieval-augmented generation, or AI agents, including use of model APIs, orchestration frameworks, and AI development tools such as Claude Code, OpenAI Codex, GitHub Copilot, or Cursor
Working knowledge of identity and access management concepts and protocols, including authentication, authorization, single sign-on, and standards such as OpenID Connect, SAML, OAuth, and JWT
Ability to travel 15 percent on average based on client needs
Ability to obtain and maintain the necessary security clearance
Authorized to work in the United States without employer sponsorship now or in the future

Technologies

Python
Claude Code
OpenAI Codex
GitHub Copilot
Cursor
Identity platforms and access management tools such as SailPoint, Okta, Microsoft Entra ID
Secrets management and IAM tooling like HashiCorp Vault, CyberArk
LangChain, LangGraph, Model Context Protocol, OPA, Cedar, OpenFGA
Cloud and automation: AWS, Microsoft Azure, Terraform, Ansible

Benefits

Discretionary annual incentive program

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2mo ago

Data Analytics Engineer

Request Technology Chicago, IL

Chicago, IL

2mo ago Closed

$100k - $130k/yr Full time Analytics Automation AWS

This position is no longer accepting applications (closed Jun 9, 2026).

Job Description

Based in Chicago with a hybrid work arrangement, the Data Analytics Engineer role at Request Technology centers on building and maintaining semantic layer data models and ETL and data serving solutions that power internal analytics. You will collaborate closely with the Data Platform, governance, and DevOps teams to support cloud infrastructure for analytics and to foster data literacy and self-service across the organization. The position offers a salary range of USD 100,000 to 130,000 per year and requires a bachelor’s or master’s degree in a quantitative discipline with at least three years of relevant experience.

Responsibilities

Build, test, and deploy semantic layer data models (virtual and physical) that simplify complex semi-structured data, reduce multiple definitions of similar data, create query-friendly datasets, and standardize column naming for downstream users developing quantitative analytics, dashboards, and internal risk applications.
Maintain performance and accuracy SLAs for the semantic layer and other data products through observability practices, ensuring proactive detection of system failures and timely incident response.
Learn user wants, motivations, priorities, and the why as part of eliciting business requirements with business users from various risk management departments.
Collaborate with upstream data producers to understand how their systems generate data and how changes over time can affect schema drift, helping to manage it effectively.
Work with Data Governance, Data Platform Team, and DBAs to design data access controls that meet business and internal governance needs.
Create documentation and testing to ensure data lineage is traceable and semantic layer components are easily discoverable and useful to business users.
Support the implementation of ETL and data serving solutions for large datasets generated by risk models, meeting latency and access-pattern SLAs critical to business users.
Promote self-service capabilities and data literacy for business users leveraging the semantic layer, analytics platforms (such as Tableau and Python), and CI/CD tools.
Invest in ongoing learning of data engineering best practices, cloud computing, the options trading industry, and financial risk management to improve maintainability, reliability, and utility of analytics infrastructure.
Assist risk analysts in solving analytics questions and provide ad-hoc development support as needed.

Requirements

Ability to collaborate with multiple partners including Business Users, Data and Solution Architects, Data Governance and IT teams (Data Platform Team, Systems & Infrastructure, Security, DevOps, Networking) to craft solutions that align business goals with internal processes, security, and delivery standards.
Ability to communicate technical concepts to audiences with varying levels of technical background and translate non-technical requests into technical outputs.
Comfortable supporting business analysts on high-priority projects.
High attention to detail, the ability to evaluate tradeoffs, and the capacity to think structurally about a solution.

Technologies

SQL
Python
Git
Tableau
Alteryx
dbt
AWS
Azure
Databricks
Snowflake
Linux shell
Docker
CyberArk
Hashi Vault
Jenkins
JFrog Artifactory
Harness
Apache Airflow
Dagster
Prefect

Benefits

401(k)
Dental insurance
Health insurance
Paid time off
Vision insurance

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