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Virtual Data Analyst Consultant Jobs in Rochester, NY

The analyst collaborates with a multidisciplinary team (e.g., clinical, financial, sales, and Line ... Analyzes data to determine business problem, trends or opportunities for process improvements.

Senior Consultant

Rochester, NY · On-site

$70K - $85K/yr

Conduct consulting fieldwork - interviews, walkthroughs, process-mapping exercises, data analysis, compliance testing, etc. * Perform testing and analytical procedures with large datasets * Write ...

SAP BODS/Data Conversion Consultant

Rochester, NY · On-site

$65.75 - $85.75/hr

... analysis for master and transactional data to improve data quality and reduce conversion risk ... Work you'll do As a Consultant, Functional Transformation on the Enterprise Performance team, you ...

Sr Compensation Analyst

Rochester, NY · On-site

$82K - $130K/yr

You will leverage advanced data analytics and market intelligence to shape competitive pay ... We provide over 21 comprehensive rewards, including medical coverage, virtual wellness classes ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate ... In this role within our Technology Consulting practice, you will leverage advanced technologies and ...

Pinion is the nation's leading food and ag consulting and accounting firm, helping clients and ... Analytical mindset with ability to synthesize data into actionable insights. * Resilience and ...

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Virtual Data Analyst Consultant information

See Rochester, NY salary details

$33.5K

$81.5K

$134.2K

How much do virtual data analyst consultant jobs pay per year?

As of Jul 26, 2026, the average yearly pay for virtual data analyst consultant in Rochester, NY is $81,538.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,700.00 and $95,700.00 per year, depending on experience, location, and employer.

What is a Virtual Data Analyst Consultant?

A Virtual Data Analyst Consultant is a professional who provides data analysis and consulting services remotely, often working with organizations to interpret complex data, generate insights, and support data-driven decision making. They use statistical tools and data visualization techniques to analyze datasets, identify trends, and present actionable recommendations to clients. These consultants typically collaborate with businesses on a project basis, offering flexible expertise without the need for on-site presence.

What are the key skills and qualifications needed to thrive as a Virtual Data Analyst Consultant, and why are they important?

To thrive as a Virtual Data Analyst Consultant, you need strong analytical skills, expertise in statistics, and a relevant degree in data science, business, or a related field. Proficiency in tools like Excel, SQL, Tableau, and programming languages such as Python or R, along with experience in cloud-based analytics platforms, is commonly required. Excellent communication, problem-solving abilities, and self-motivation set top consultants apart in remote environments. These skills enable effective data-driven decision-making and seamless client collaboration regardless of location.

What is the difference between Virtual Data Analyst Consultant vs Virtual Data Scientist?

AspectVirtual Data Analyst ConsultantVirtual Data Scientist
Required CredentialsBachelor's in Data Analysis, Statistics, or related field; certifications like Microsoft Excel, TableauBachelor's or higher in Data Science, Computer Science, or related; certifications like Python, R, or Machine Learning
Work EnvironmentRemote or client-site, project-based, consulting firms or freelanceRemote or on-site, research-focused, tech companies or consulting
Employer & Industry UsageConsulting firms, finance, marketing, healthcareTech companies, research institutions, finance, healthcare

While both roles involve working with data remotely, Virtual Data Analyst Consultants focus on analyzing data to provide actionable insights for clients, often using tools like Excel and Tableau. Virtual Data Scientists, on the other hand, develop complex models and algorithms using programming languages like Python or R to uncover deeper patterns. The roles overlap in data handling but differ in technical depth and scope.

How does a Virtual Data Analyst Consultant typically collaborate with clients and internal teams while working remotely?

As a Virtual Data Analyst Consultant, effective communication and collaboration are essential since you’ll often work with clients and cross-functional teams in a remote environment. You’ll regularly participate in virtual meetings, share updates through project management tools, and use cloud-based platforms to access and analyze data. Building strong working relationships remotely involves proactive status reporting, clarifying project expectations, and being responsive to feedback. Staying organized and transparent helps ensure alignment, even when team members are in different locations or time zones.
What are the most commonly searched types of Data Analyst Consultant jobs in Rochester, NY? The most popular types of Data Analyst Consultant jobs in Rochester, NY are:
What cities near Rochester, NY are hiring for Virtual Data Analyst Consultant jobs? Cities near Rochester, NY with the most Virtual Data Analyst Consultant job openings:
Data Engineer - Project Delivery Analyst

Data Engineer - Project Delivery Analyst

Deloitte

Rochester, NY • On-site

Other

Posted 6 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 91 frontline employees who took The Breakroom Quiz

58th of 150 rated financial services


Job description

Are you an experienced, passionate pioneer in technology who wants to work in a collaborative environment? As an experienced Data Engineer - Project Delivery Analyst you will have the ability to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. If so, consider an opportunity with Deloitte under our Project Delivery Talent Model. Project Delivery Model (PDM) is a talent model that is tailored specifically for long-term, onsite client service delivery.

Recruiting for this role ends on July 30th, 2026.

Work you'll do/Responsibilities  

You will support a Data & Analytics Foundry across numerous business product teams (scaled program with ~235 onshore/offshore resources), building reliable pipelines and curated datasets for analytics and downstream consumption.

  • Build and enhance data pipelines on AWS using Python to ingest, transform, and deliver data to Snowflake and downstream consumers.
  • Develop and maintain Snowflake objects (schemas, tables, views) and performant SQL transformations to produce curated, analytics-ready datasets.
  • Implement workflow automation and scheduling (e.g., Airflow/MWAA, Step Functions, Glue) with proper dependencies, retries, and logging.
  • Apply data quality checks and basic observability (validation rules, reconciliation, alerts) and support incident triage and remediation.
  • Optimize pipeline and query performance with guidance (efficient Python, partitioning/file formats in S3, Snowflake warehouse usage and query tuning).
  • Follow CI/CD and IaC standards (e.g., Git-based workflows, Terraform/CloudFormation changes) to promote code across environments.
  • Collaborate with analysts, product owners, and source-system teams to clarify requirements and validate outputs; participate in sprint ceremonies and estimations.
  • Contribute to code reviews (give/receive), unit tests, and peer debugging; learn and apply team engineering standards.
  • Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
  • Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes

The Team 

AI& Data - AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Qualifications

Required

  • 1+ year of experience building/enhancing data pipelines and curated datasets for analytics/downstream consumers.
  • 1+ year of hands-on experience with SQL and Python, including Snowflake and/or PySpark for transformations and scalable processing.
  • 1+ year of experience with cloud data engineering on AWS (preferred) or Azure/GCP, including orchestration/scheduling (e.g., Airflow/MWAA, Step Functions, Glue, ADF/Fabric Data Factory).
  • Understanding of ELT patterns and Lakehouse/warehouse concepts; familiarity with S3 file formats/partitioning (e.g., Parquet/Delta).
  • Working knowledge of DevOps practices (Git-based workflows, CI/CD) and exposure to Infrastructure-as-Code (Terraform/CloudFormation).
  • Understanding data quality, basic observability, and metadata/governance fundamentals.
  • Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience.
  • Limited immigration sponsorship may be available.
  • Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve.

Preferred

  • Agile delivery experience .
  • Analytical ability to manage multiple projects and prioritize tasks into manageable work products.
  • Can operate independently or with minimum supervision.
  • Excellent written and communication skills.
  • Ability to deliver technical demonstrations.

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 $57,300 to $95,500.

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.

Qualifications:

Are you an experienced, passionate pioneer in technology who wants to work in a collaborative environment? As an experienced Data Engineer - Project Delivery Analyst you will have the ability to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. If so, consider an opportunity with Deloitte under our Project Delivery Talent Model. Project Delivery Model (PDM) is a talent model that is tailored specifically for long-term, onsite client service delivery.

Recruiting for this role ends on July 30th, 2026.

Work you'll do/Responsibilities  

You will support a Data & Analytics Foundry across numerous business product teams (scaled program with ~235 onshore/offshore resources), building reliable pipelines and curated datasets for analytics and downstream consumption.

  • Build and enhance data pipelines on AWS using Python to ingest, transform, and deliver data to Snowflake and downstream consumers.
  • Develop and maintain Snowflake objects (schemas, tables, views) and performant SQL transformations to produce curated, analytics-ready datasets.
  • Implement workflow automation and scheduling (e.g., Airflow/MWAA, Step Functions, Glue) with proper dependencies, retries, and logging.
  • Apply data quality checks and basic observability (validation rules, reconciliation, alerts) and support incident triage and remediation.
  • Optimize pipeline and query performance with guidance (efficient Python, partitioning/file formats in S3, Snowflake warehouse usage and query tuning).
  • Follow CI/CD and IaC standards (e.g., Git-based workflows, Terraform/CloudFormation changes) to promote code across environments.
  • Collaborate with analysts, product owners, and source-system teams to clarify requirements and validate outputs; participate in sprint ceremonies and estimations.
  • Contribute to code reviews (give/receive), unit tests, and peer debugging; learn and apply team engineering standards.
  • Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
  • Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes

The Team 

AI& Data - AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Qualifications

Required

  • 1+ year of experience building/enhancing data pipelines and curated datasets for analytics/downstream consumers.
  • 1+ year of hands-on experience with SQL and Python, including Snowflake and/or PySpark for transformations and scalable processing.
  • 1+ year of experience with cloud data engineering on AWS (preferred) or Azure/GCP, including orchestration/scheduling (e.g., Airflow/MWAA, Step Functions, Glue, ADF/Fabric Data Factory).
  • Understanding of ELT patterns and Lakehouse/warehouse concepts; familiarity with S3 file formats/partitioning (e.g., Parquet/Delta).
  • Working knowledge of DevOps practices (Git-based workflows, CI/CD) and exposure to Infrastructure-as-Code (Terraform/CloudFormation).
  • Understanding data quality, basic observability, and metadata/governance fundamentals.
  • Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience.
  • Limited immigration sponsorship may be available.
  • Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve.

Preferred

  • Agile delivery experience .
  • Analytical ability to manage multiple projects and prioritize tasks into manageable work products.
  • Can operate independently or with minimum supervision.
  • Excellent written and communication skills.
  • Ability to deliver technical demonstrations.

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 $57,300 to $95,500.

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.

Education:Bachelor's DegreeEmployment Type:

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