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Senior Data Engineer Jobs in Ivoryton, CT (NOW HIRING)

The Rockridge Group

Senior Data Engineer

New Haven, CT · Hybrid

$106K - $144K/yr

Senior Data Engineer Location: 50 Mitchell Dr Suite 105, New Haven, CT 06511 Salary: $ 130-145K Work Status: Hybrid Job Summary: Company X is seeking a savvy Data Engineer to join our growing team of ...

Connecticut Water Service

Senior Engineer

Cromwell, CT · On-site

$105K - $145K/yr

We have an opening in our Engineering department for a Senior Engineer . We are passionate about ... Gather and analyze water use data. Design water storage tanks or other water storage facilities.

Connecticut Water Co.

Senior Engineer

Cromwell, CT

$105K - $145K/yr

The Senior Engineer is responsible for providing excellent service to our customers, shareholders ... Gather and analyze water use data. Design water storage tanks or other water storage facilities.

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All JobsData Engineer JobsSenior Data Engineer JobsSenior Data Engineer Jobs in Ivoryton, CT

Senior Data Engineer information

See Ivoryton, CT salary details

$79.8K

$124.5K

$172.5K

How much do senior data engineer jobs pay per year?

As of Sep 1, 2026, the average yearly pay for senior data engineer in Ivoryton, CT is $124,508.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,500.00 and $141,900.00 per year, depending on experience, location, and employer.

What is a senior data engineer?

Senior Data Engineers are experienced professionals who design, build, and maintain large-scale data processing systems and infrastructure. They are responsible for developing data pipelines, managing databases, and ensuring the efficient flow and integrity of data across various platforms. Senior Data Engineers often collaborate with data scientists, analysts, and other engineers to support business intelligence and machine learning projects. They also play a key role in implementing best practices for data security, quality, and governance within an organization.

What are some common challenges senior data engineers face when integrating data from multiple sources?

Senior Data Engineers often encounter challenges such as inconsistent data formats, varying data quality, and differing update frequencies when integrating data from multiple sources. Addressing these issues requires designing robust ETL (Extract, Transform, Load) pipelines, implementing data validation checks, and collaborating closely with source system owners to ensure data integrity. Effective communication with cross-functional teams and leveraging scalable data integration tools are also essential to streamline the process and minimize errors.

What are the key skills and qualifications needed to thrive as a senior data engineer, and why are they important?

To thrive as a Senior Data Engineer, you need strong expertise in data modeling, ETL development, programming (such as Python or Scala), and a degree in computer science or a related field. Proficiency with big data technologies (like Hadoop, Spark), cloud platforms (AWS, Azure, GCP), and database systems, as well as relevant certifications, is highly valuable. Excellent problem-solving, communication, and leadership skills help you collaborate across teams and mentor junior engineers. These skills and qualities ensure robust, scalable data solutions that support organizational decision-making and growth.

What is the difference between Senior Data Engineer vs Data Scientist?

AspectSenior Data EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, Engineering, or related; experience with data pipelinesBachelor's/Master's in CS, Statistics, or related; proficiency in statistical analysis and modeling
Work EnvironmentBuild and maintain data infrastructure, optimize data workflowsAnalyze data, develop predictive models, generate insights
Employer & Industry UsageTech companies, finance, healthcare, where data engineering is essentialResearch, marketing, tech firms focusing on data analysis and modeling

While both roles work with data, Senior Data Engineers focus on developing and maintaining data infrastructure, whereas Data Scientists analyze data to generate insights and build models. They often collaborate but have distinct skill sets and responsibilities.

What do senior data engineers do?

Senior data engineers design, build, and maintain large-scale data pipelines and infrastructure to support data collection, storage, and analysis. They often work with tools like SQL, Spark, and cloud platforms, and may lead data team projects while ensuring data quality and security.

What cities near Ivoryton, CT are hiring for Senior Data Engineer jobs?

Cities near Ivoryton, CT with the most Senior Data Engineer job openings:

Senior Data Engineer jobs near you
Infographic showing various Senior Data Engineer job openings in Ivoryton, CT as of June 2026, with employment types broken down into 1% As Needed, 92% Full Time, 4% Part Time, and 3% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $124,508 per year, or $59.9 per hour.

Senior Data Engineer

The Rockridge Group

New Haven, CT • Hybrid

$106K - $144K/yr

Full-time

Re-posted 19 days ago

Job description

Job Title: Senior Data Engineer
Location: 50 Mitchell Dr Suite 105, New Haven, CT 06511
Salary: $ 130-145K
Work Status: Hybrid
 
Job Summary: 
 
Company X is seeking a savvy Data Engineer to join our growing team of analytics experts. The position is responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. The Data Engineer will support our software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout the organization. We are seeking a candidate who is self-directed and comfortable supporting the data needs of multiple teams, systems, and products. The right candidate will be excited by the prospect of optimizing and re-designing our company’s data architecture to support our next generation of data initiatives.
 
What You’ll Do:
 
  • Develop and maintain scalable data pipelines and build out new API integrations to support a data environment increasing in volume and complexity
  • Collaborate with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility, and fostering data-driven decision making across the organization
  • Implement processes and tools to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it
  • Perform data analysis required to troubleshoot data related issues and assist in the resolution of data issues
  • Work closely with all business units and data engineering teams to develop strategy for long term data platform architecture
  • Write unit/integration tests and contributes to integration documentation
  • Contribute to the design of data integrations and data quality framework
 
Required
 
  • Bachelor's Degree in Business, Math, Computer Science, Quantitative Business Analysis, or related field
  • 5+ years of directly related work experience
  • Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases
  • Experience building and optimizing ‘big data’ data pipelines, architectures, and data sets
  • Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
  • Strong analytic skills related to working with unstructured datasets
 
 
Preferred
 
  • A successful history of manipulating, processing, and extracting value from large datasets
  • Strong project management and organizational skills
  • Experience supporting and working with cross-functional teams in a dynamic environment
  • Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores