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Internship Azure Data Engineer Jobs in Rochester, NY

AI Data Engineer - Senior Consultant

Rochester, NY · Hybrid

$103.10K - $141.60K/yr

... on AWS/Azure/GCP (one or more), including managed data platforms and scalable compute patterns ... AI Engineer Senior Consultant Our Deloitte Human Capital team transforms technology platforms ...

AI Data Engineer - Senior Consultant

Rochester, NY · On-site

$104.60K - $142.10K/yr

... Azure/GCP (one or more), including managed data platforms and scalable compute patterns. • 4+ ... ML, data engineering, platform, and security. • 4+ years of experience with treat testing ...

Data Scientist II

Pittsford, NY · On-site

$99.20K - $124K/yr

Honeywell is looking for a data driven professional to join its Data Science engineering team to ... Some exposure to using cloud services from AWS, Azure, or GCP to develop solutions. * Awareness of ...

Data Scientist II

Pittsford, NY · Hybrid

$99.20K - $124K/yr

Honeywell is looking for a data driven professional to join its Data Science engineering team to ... Some exposure to using cloud services from AWS, Azure, or GCP to develop solutions. * Awareness of ...

Data Scientist II

Pittsford, NY · Hybrid

$99.20K - $124K/yr

Honeywell is looking for a data driven professional to join its Data Science engineering team to ... Some exposure to using cloud services from AWS, Azure, or GCP to develop solutions. * Awareness of ...

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Internship Azure Data Engineer information

See Rochester, NY salary details

$13

$25

$38

How much do internship azure data engineer jobs pay per hour?

As of May 29, 2026, the average hourly pay for internship azure data engineer in Rochester, NY is $25.08, according to ZipRecruiter salary data. Most workers in this role earn between $20.38 and $28.46 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Internship Azure Data Engineer, and why are they important?

To thrive as an Internship Azure Data Engineer, you need a solid understanding of data management concepts, SQL, and a background in computer science or a related field. Familiarity with Microsoft Azure services like Azure Data Factory, Azure SQL Database, and tools such as Power BI is typically required, along with a willingness to pursue certifications like Microsoft Certified: Azure Data Engineer Associate. Strong analytical thinking, problem-solving skills, and effective teamwork set candidates apart in this role. These skills are essential to efficiently design, implement, and maintain data solutions that support business intelligence and decision-making in cloud environments.

What kinds of projects and technologies can I expect to work with during an Azure Data Engineer internship?

As an Azure Data Engineer intern, you'll typically gain hands-on experience with cloud data solutions, such as building and managing data pipelines using Azure Data Factory, integrating data sources with Azure Databricks or Synapse Analytics, and working with Azure SQL databases. Interns often participate in real-world projects like data migration, data cleansing, and developing dashboards for business insights. You will likely collaborate closely with data scientists, software developers, and business analysts, learning best practices for data security, scalability, and performance in a cloud environment.

What does an Internship Azure Data Engineer do?

An Internship Azure Data Engineer assists in designing, building, and maintaining data solutions using Microsoft Azure technologies. Responsibilities typically include working with data pipelines, cloud databases, and tools such as Azure Data Factory, Azure SQL Database, and Azure Databricks. Interns often help with data integration, transformation, and storage tasks, as well as collaborating with senior engineers and stakeholders to support data-driven projects. This role provides valuable exposure to cloud computing, big data, and the practical application of data engineering concepts.

What is the difference between Internship Azure Data Engineer vs Data Analyst Intern?

AspectInternship Azure Data EngineerData Analyst Intern
Required CredentialsBasic knowledge of Azure, SQL, and data engineering conceptsBasic understanding of data analysis, Excel, and SQL
Work EnvironmentCloud platforms, data pipelines, and database managementData visualization, reporting, and data interpretation
Employer & Industry UsageTech companies, cloud service providers, data-driven organizationsBusiness, marketing, finance sectors, and consulting firms

Internship Azure Data Engineer roles focus on cloud-based data pipeline development and management using Azure tools, while Data Analyst Internships emphasize data interpretation and reporting. Both roles are entry-level, often require SQL knowledge, and serve data-driven industries, but they differ in technical focus and daily tasks.

What are popular job titles related to Internship Azure Data Engineer jobs in Rochester, NY? For Internship Azure Data Engineer jobs in Rochester, NY, the most frequently searched job titles are:
What job categories do people searching Internship Azure Data Engineer jobs in Rochester, NY look for? The top searched job categories for Internship Azure Data Engineer jobs in Rochester, NY are:
What cities near Rochester, NY are hiring for Internship Azure Data Engineer jobs? Cities near Rochester, NY with the most Internship Azure Data Engineer job openings:
AI Data Engineer - Senior Consultant

AI Data Engineer - Senior Consultant

Deloitte

Rochester, NY • Hybrid

$103.10K - $141.60K/yr

Other

Posted 11 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

59th of 138 rated financial services


Job description

AI Engineer Senior Consultant

Our Deloitte Human Capital team transforms technology platforms, drives innovation, and helps make a significant impact on our clients' success. We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that power Human Capital AI products and analytics. You will work with an AI Data Engineer (data ingestion, curation, governance, platform foundations) and a Lead AI Solutions Architect (end-to-end solution architecture, integration patterns, non-functional requirements), partnering closely with product, data science/ML, security, and platform engineering to deliver reliable, secure, and scalable AI solutions.

This role is hands-on and delivery-oriented: you will ship production pipelines and services that support model training, real-time inference, and LLM applications using Claude-, GPT/Codex-, and Gemini-class models, and more implemented with strong governance, observability, and cost/performance discipline.

Recruiting for this role ends on August 30, 2026

Work You'll Do:

As an AI Engineer Senior Consultant, you will design, build, and run the trusted, governed data + feature + retrieval layer used by AI/ML and GenAI solutions. You will deliver reproducible datasets and features, operationalize quality and lineage, and enable secure consumption patterns for both predictive ML and LLM-based experiences.

Key Responsibilities:

  • Partner with the Lead AI Solutions Architect and AI Data Engineer to translate Human Capital product needs into secure, scalable technical designs and delivered solutions (APIs, services, pipelines, containers/serverless) meeting availability, performance, and security expectations.
  • Build and operationalize LLM-enabled capabilities (e.g., copilots, HR knowledge assistants, summarization, policy Q&A) using Claude/GPT(Codex)/Gemini, including secure endpoints, tool/function calling, and reusable prompt/context patterns.
  • Implement LLM application patterns including RAG, document ingestion/chunking, embeddings, vector/hybrid search, and retrieval/evaluation telemetry.
  • Deliver governed datasets and feature engineering/serving for ML training and real-time inference (online/offline consistency, caching, latency SLOs, backfills).
  • Implement safety, privacy, and access controls (PII handling, prompt-injection defenses, content filtering, policy-based access) with security and risk stakeholders.
  • Establish data/model reliability and cost-performance discipline (data quality, schema evolution, lineage/metadata, monitoring; right-sizing, query tuning, LLM token/cost telemetry).
  • Contribute to MLOps/LLMOps and production operations (versioning, reproducibility, CI/CD, automated testing, observability, incident response); support design reviews, deployment readiness, and runbooks.

The Team

HC Forward is a dedicated innovation partner accelerating the future of Human Capital by building market-aligned products, platforms, and services that apply AI, data, and engineering to modernize HR experiences and outcomes.

Required Qualifications:

  • Bachelor's degree in a STEM field (e.g., Computer Science, Engineering, Statistics, Data Science)
  • 4+ years building and delivering LLM/GenAI solutions with Claude/GPT(Codex)/Gemini-class models, including prompt/context design, tool/function calling, evaluation, and production integration.
  • 4+ years implementing RAG/retrieval (document processing, embeddings, vector/hybrid search) with enterprise governance controls.
  • 4+ years of modern data & AI engineering, including data modeling, batch/streaming pipelines, structured/unstructured processing, and feature engineering/serving fundamentals.
  • 4+ years building production, real-time inference services (API design, latency/performance, reliability patterns).
  • 4+ years leading platform/integration engineering across enterprise systems; strong API/integration experience (REST, GraphQL, event-driven, microservices, middleware).
  • 4+ years DevOps/DevSecOps experience (CI/CD, IaC such as Terraform/CloudFormation, Docker/Kubernetes, observability/monitoring).
  • 4+ years leading security/compliance efforts; familiarity with enterprise security controls (IAM, encryption, secrets, audit logging) and data/privacy (PII, retention, access controls); SOC 2/GDPR/HIPAA exposure a plus.
  • Ability to travel 0-25%, on average, based on client and project needs.
  • Limited immigration sponsorship may be available

Preferred Qualifications:

  • Advanced degree (MS/PhD) and/or relevant certifications (cloud and AI/ML).
  • 4+ years of experience with Human Capital platforms and integrations (e.g., Workday, SAP SuccessFactors, Oracle HCM, Salesforce) and HR data domains.
  • 4+ years of experience operationalizing LLMOps/MLOps capabilities (evaluation, monitoring, governance workflows, model/prompt/version management).
  • 4+ years of cloud experience on AWS/Azure/GCP (one or more), including managed data platforms and scalable compute patterns.
  • 4+ years of experience with structured problem solving, translating business needs into requirements, acceptance criteria, and shippable increments.
  • 4+ years of experience with stakeholder communication: ability to explain AI/GenAI trade-offs (quality vs. latency vs. cost vs. risk) and document decisions.
  • 4+ years of experience collaborating across product, data science/ML, data engineering, platform, and security.
  • 4+ years of experience with treat testing, monitoring, and operational readiness as core responsibilities.
  • 4+ years of experience with ethics and privacy awareness being able to recognize consent/PII/bias boundaries and escalate appropriately.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $113,100 to $208,300.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Possible Locations: Atlanta, Austin, Baltimore, Boston, Charlotte, Chicago, Cincinnati, Cleveland, Columbus, Costa Mesa, Dallas, Denver, Detroit, Hartford, Houston, Indianapolis, Jacksonville, Kansas City, Las Vegas, Los Angeles, McLean, Miami, Milwaukee, Nashville, New Orleans, New York, Philadelphia, Pittsburgh, Portland, Raleigh, Richmond, Sacramento, San Antonio, San Diego, San Francisco, San Jose, Seattle, St. Louis, Stamford, Tampa, Tempe

Information for applicants with a need for accommodation: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applicants.html

For more information about Human Capital, visit our landing page at: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-human-capital-consulting-jobs.html

#HCFY26 #IIOFY26

Qualifications:

AI Engineer Senior Consultant

Our Deloitte Human Capital team transforms technology platforms, drives innovation, and helps make a significant impact on our clients' success. We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that power Human Capital AI products and analytics. You will work with an AI Data Engineer (data ingestion, curation, governance, platform foundations) and a Lead AI Solutions Architect (end-to-end solution architecture, integration patterns, non-functional requirements), partnering closely with product, data science/ML, security, and platform engineering to deliver reliable, secure, and scalable AI solutions.

This role is hands-on and delivery-oriented: you will ship production pipelines and services that support model training, real-time inference, and LLM applications using Claude-, GPT/Codex-, and Gemini-class models, and more implemented with strong governance, observability, and cost/performance discipline.

Recruiting for this role ends on August 30, 2026

Work You'll Do:

As an AI Engineer Senior Consultant, you will design, build, and run the trusted, governed data + feature + retrieval layer used by AI/ML and GenAI solutions. You will deliver reproducible datasets and features, operationalize quality and lineage, and enable secure consumption patterns for both predictive ML and LLM-based experiences.

Key Responsibilities:

  • Partner with the Lead AI Solutions Architect and AI Data Engineer to translate Human Capital product needs into secure, scalable technical designs and delivered solutions (APIs, services, pipelines, containers/serverless) meeting availability, performance, and security expectations.
  • Build and operationalize LLM-enabled capabilities (e.g., copilots, HR knowledge assistants, summarization, policy Q&A) using Claude/GPT(Codex)/Gemini, including secure endpoints, tool/function calling, and reusable prompt/context patterns.
  • Implement LLM application patterns including RAG, document ingestion/chunking, embeddings, vector/hybrid search, and retrieval/evaluation telemetry.
  • Deliver governed datasets and feature engineering/serving for ML training and real-time inference (online/offline consistency, caching, latency SLOs, backfills).
  • Implement safety, privacy, and access controls (PII handling, prompt-injection defenses, content filtering, policy-based access) with security and risk stakeholders.
  • Establish data/model reliability and cost-performance discipline (data quality, schema evolution, lineage/metadata, monitoring; right-sizing, query tuning, LLM token/cost telemetry).
  • Contribute to MLOps/LLMOps and production operations (versioning, reproducibility, CI/CD, automated testing, observability, incident response); support design reviews, deployment readiness, and runbooks.

The Team

HC Forward is a dedicated innovation partner accelerating the future of Human Capital by building market-aligned products, platforms, and services that apply AI, data, and engineering to modernize HR experiences and outcomes.

Required Qualifications:

  • Bachelor's degree in a STEM field (e.g., Computer Science, Engineering, Statistics, Data Science)
  • 4+ years building and delivering LLM/GenAI solutions with Claude/GPT(Codex)/Gemini-class models, including prompt/context design, tool/function calling, evaluation, and production integration.
  • 4+ years implementing RAG/retrieval (document processing, embeddings, vector/hybrid search) with enterprise governance controls.
  • 4+ years of modern data & AI engineering, including data modeling, batch/streaming pipelines, structured/unstructured processing, and feature engineering/serving fundamentals.
  • 4+ years building production, real-time inference services (API design, latency/performance, reliability patterns).
  • 4+ years leading platform/integration engineering across enterprise systems; strong API/integration experience (REST, GraphQL, event-driven, microservices, middleware).
  • 4+ years DevOps/DevSecOps experience (CI/CD, IaC such as Terraform/CloudFormation, Docker/Kubernetes, observability/monitoring).
  • 4+ years leading security/compliance efforts; familiarity with enterprise security controls (IAM, encryption, secrets, audit logging) and data/privacy (PII, retention, access controls); SOC 2/GDPR/HIPAA exposure a plus.
  • Ability to travel 0-25%, on average, based on client and project needs.
  • Limited immigration sponsorship may be available

Preferred Qualifications:

  • Advanced degree (MS/PhD) and/or relevant certifications (cloud and AI/ML).
  • 4+ years of experience with Human Capital platforms and integrations (e.g., Workday, SAP SuccessFactors, Oracle HCM, Salesforce) and HR data domains.
  • 4+ years of experience operationalizing LLMOps/MLOps capabilities (evaluation, monitoring, governance workflows, model/prompt/version management).
  • 4+ years of cloud experience on AWS/Azure/GCP (one or more), including managed data platforms and scalable compute patterns.
  • 4+ years of experience with structured problem solving, translating business needs into requirements, acceptance criteria, and shippable increments.
  • 4+ years of experience with stakeholder communication: ability to explain AI/GenAI trade-offs (quality vs. latency vs. cost vs. risk) and document decisions.
  • 4+ years of experience collaborating across product, data science/ML, data engineering, platform, and security.
  • 4+ years of experience with treat testing, monitoring, and operational readiness as core responsibilities.
  • 4+ years of experience with ethics and privacy awareness being able to recognize consent/PII/bias boundaries and escalate appropriately.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $113,100 to $208,300.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Possible Locations: Atlanta, Austin, Baltimore, Boston, Charlotte, Chicago, Cincinnati, Cleveland, Columbus, Costa Mesa, Dall...


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