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Data Engineer Jobs in Rochester, NY (NOW HIRING)

Pwc

NGA AI Engineer Manager

Rochester, NY

$73K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Element Materials Technology

Data Processor

Geneseo, NY · On-site

Element has an opportunity for a Data Processor to join our rapidly expanding team. As a member of ... Propose engineering documents for clients' approval, on-site installation and hands-on monitoring ...

Lthc

AI Engineer I/II

Rochester, NY · On-site

Collaborates with data engineering teams to acquire, clean, and prepare data for model training. * Supports model evaluation, testing, and performance monitoring in pre-production environments.

Lthc

AI Engineer I/II

Rochester, NY

Collaborates with data engineering teams to acquire, clean, and prepare data for model training. * Supports model evaluation, testing, and performance monitoring in pre-production environments.

Lthc

AI Engineer I/II

Rochester, NY

Collaborates with data engineering teams to acquire, clean, and prepare data for model training. * Supports model evaluation, testing, and performance monitoring in pre-production environments.

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All JobsData Engineer JobsData Engineer Jobs in Rochester, NY

Data Engineer information

See Rochester, NY salary details

$43.9K

$128K

$175.2K

How much do data engineer jobs pay per year?

As of Jul 9, 2026, the average yearly pay for data engineer in Rochester, NY is $128,021.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,000.00 and $135,700.00 per year, depending on experience, location, and employer.

Is a data engineer a difficult job?

A data engineer role involves designing, building, and maintaining data pipelines and infrastructure, which requires strong programming skills, knowledge of databases, and familiarity with tools like SQL, Python, and cloud platforms. The job can be challenging due to the complexity of managing large-scale data systems and ensuring data quality and security, but it is manageable with proper training and experience.

What is the difference between Data Engineer vs Data Scientist?

AspectData EngineerData Scientist
Primary FocusBuilding and maintaining data pipelines and infrastructureAnalyzing data to extract insights and create models
SkillsSQL, ETL, programming (Python, Java), database managementStatistics, machine learning, data analysis, programming (Python, R)
Work EnvironmentData warehouses, cloud platforms, backend systemsData analysis environments, research labs, visualization tools
Common ToolsApache Spark, Hadoop, Airflow, SQLJupyter, RStudio, Tableau, scikit-learn

Data Engineers focus on creating and maintaining the infrastructure that allows data to be collected, stored, and processed efficiently. Data Scientists analyze this data to generate insights, build predictive models, and support decision-making. While their skills overlap, Data Engineers are more involved in data pipeline development, whereas Data Scientists focus on data analysis and modeling.

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

To thrive as a Data Engineer, you need a strong background in computer science, data modeling, and programming languages such as Python or Java, often coupled with a relevant degree. Familiarity with ETL tools, big data frameworks (like Hadoop or Spark), and cloud platforms (such as AWS or Azure) is typically required, along with certifications like AWS Certified Data Analytics. Strong problem-solving skills, attention to detail, and effective communication set exceptional data engineers apart. These skills and qualities are essential for building robust data pipelines, ensuring data quality, and supporting data-driven decision-making across organizations.

What Does a Data Engineer Do?

The job duties of a data engineer involve helping with the development of systems, software, and infrastructure used to process, store and analyze data. Your responsibilities in this career include working to install data management software. Your employer may expect you to perform maintenance and install updates to all software and systems that they use for data acquisition, management, and analysis. Data engineers also analyze existing data systems to find ways to improve efficiency and accessibility. You then suggest upgrades or changes based on your assessment.

What are Data Engineers?

Data Engineers are IT professionals who design, construct, install, and maintain large-scale processing systems and other infrastructure for collecting, storing, and analyzing data. They build and optimize data pipelines and architectures that allow organizations to efficiently access and use data for business insights. Data Engineers work closely with data scientists, analysts, and other stakeholders to ensure that data is reliable, accessible, and secure. Their responsibilities often include working with databases, cloud platforms, and big data tools.

How do Data Engineers typically collaborate with Data Scientists and Analysts within an organization?

Data Engineers play a crucial role in ensuring that Data Scientists and Analysts have reliable, well-structured data for their projects. This collaboration often involves building and maintaining data pipelines, optimizing data storage solutions, and troubleshooting data quality issues. Regular communication and agile teamwork are common, with Data Engineers frequently participating in meetings to understand analytical requirements and adjust data processes accordingly. By working closely together, these teams can quickly iterate on data models and deliver actionable insights to drive business decisions.

What does a data engineer actually do?

A data engineer designs, builds, and maintains the infrastructure and pipelines that enable organizations to collect, store, and process large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible, reliable, and ready for analysis by data scientists and analysts.

Is a data engineer entry level?

Data engineering is typically an intermediate to senior role that requires experience with programming, databases, and data pipelines. Entry-level positions may be available for those with relevant internships, certifications, or strong foundational skills in SQL, Python, or cloud platforms, but most roles expect prior experience or demonstrated technical competence.

What engineer makes $500,000 a year?

Senior data engineers with extensive experience, advanced skills in big data tools, and certifications can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within large tech companies. Such compensation often includes bonuses, stock options, and other incentives. These roles typically require strong programming, cloud platform expertise, and a deep understanding of data architecture.
More about Data Engineer jobs
What are the most commonly searched types of Data Engineer jobs in Rochester, NY? The most popular types of Data Engineer jobs in Rochester, NY are:
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What job categories do people searching Data Engineer jobs in Rochester, NY look for? The top searched job categories for Data Engineer jobs in Rochester, NY are:
What cities near Rochester, NY are hiring for Data Engineer jobs? Cities near Rochester, NY with the most Data Engineer job openings:
Data Engineer jobs near you
AIA Senior Developer

AIA Senior Developer

Avani Technology Solutions, Inc.

York, NY • On-site

Contractor

Re-posted 18 days ago

Job description

. Job Title :Cognizant is looking for Sr Developer role 2. Job Summary :- Create and maintain optimal data pipeline architecture assemble large complex data sets that meet functional / non-functional business requirements. - Collaborate with and across Agile teams to design develop test implement and support technical solutions in full-stack development tools and technologies - Utilize programming languages like Python and Open-Source RDBMS and NoSQL databases and Cloud based data warehousing services such as Snowflake 3. Shift :9 am to 6 pm EST 4. Roles & Responsibilities :- Share your passion for staying on top of tech trends experimenting with and learning new technologies participating in internal & external technology communities and mentoring other members of the engineering community - Collaborate with digital product managers and deliver robust cloud-based solutions that drive powerful experiences to help millions of Americans achieve financial empowerment - Perform unit tests and conducting reviews with other team members to make sure your code is rigorously designed elegantly coded and effectively tuned for performance . - 4+ years of experience (Sr-level) Strong Python Programming - 4+ years of experience (Mid-level) Experience with Spark Ecosystem: PySpark Kafka etc - 1+ years of strong technical Experience with AWS cloud services like S3 IAM EC2 EMR RDS Redshift CloudWatch - 1+ years of experience with GitHub Jenkins CICD - Experience with stream-processing frameworks: Storm Spark-Streaming etc. - 1+ Years of experience with relational SQL Snowflake and NoSQL databases including Postgres and Cassandra. - Mandatory Skills Required: Python PySpark AWS (S3 IAM EC2 EMR RDS) GitHub Jenkins CICD Snowflake SQL UNIX - Optional Skills Required: Kafka Spark-Streaming AWS Glue NoSQL databases Data Warehouse experience .Certifications Required :AWS & Snowflake. 5. Demand requires Travel? :No 6. Certification(s) Required :AWS & Snowflake
Hours : 8:00am to 5:00pm
Education :
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