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Kafka Engineer Jobs in Springfield, MA (NOW HIRING)

Teamware Solutions

DATA Engineer

East Hartford, CT · On-site

$113K - $136K/yr

Mentor junior engineers and conduct code reviews to uphold engineering best practices * Partner ... Knowledge of streaming technologies (Kafka, Event Hubs) * Familiarity with Great Expectations or ...

Appex Innovation

Salesforce - Health Cloud

Hartford, CT · On-site

$50 - $55/hr

FHIR/HL7 integrations, * event-driven architecture (Kafka) * Data Cloud experience preferred * Experience building Agentforce solutions and AI-powered agents. * Experience with Salesforce DevOps and ...

New

Appex Innovation

Salesforce - Health Cloud

Hartford, CT

$56 - $74.25/hr

... Kafka) Data Cloud experience preferred Experience building Agentforce solutions and AI-powered agents. Experience with Salesforce DevOps and CI/CD tools (Git, AutoRABIT/Copado, Salesforce CLI)

New

CVS Health

Software Development Engineer

Hartford, CT · On-site

$79K - $158K/yr

Familiarity with messaging/event streaming (e.g., Kafka) and scalable integration patterns. * Interest/experience using AI tools to improve developer productivity, test generation, or building small ...

CVS Health

Senior Data Engineer

Hartford, CT · On-site

$106K - $145K/yr

As a Senior Data Engineer, you will be instrumental in designing, developing, and maintaining ... Azure Event Hubs, Azure Functions, Kafka, Spark Streaming) * 1+ year(s) of soliciting complex ...

Travelers

Sr Software Engineer

Hartford, CT · On-site

$139K - $230K/yr

Travelers is seeking a Senior Software Engineer to join our organization as we grow and transform ... Understanding of and experience with eventing systems (e.g., Kafka) * Experience with relational ...

The Whiteside Agency

Sr Software Engineer

Hartford, CT

$139K - $230K/yr

Travelers is seeking a Senior Software Engineer to join our organization as we grow and transform ... Understanding of and experience with eventing systems (e.g., Kafka) * Experience with relational ...

HR Pundits

Salesforce Technical Lead Health Cloud

Hartford, CT · On-site

$69.50 - $86.25/hr

FHIR/HL7 integrations, * event-driven architecture (Kafka) * Data Cloud experience preferred * Experience building Agentforce solutions and AI-powered agents. * Experience with Salesforce DevOps and ...

New

The Hartford

Senior Staff Data Engineer

Hartford, CT · Hybrid

$135K - $202K/yr

Research, experiment, and utilize leading big data methodologies (AWS, Hadoop/EMR, Spark, Kafka ... of data engineering experience and best practices in Distributed systems, Data warehousing ...

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All JobsKafka Engineer JobsKafka Engineer Jobs in Springfield, MA

Kafka Engineer information

See Springfield, MA salary details

$38.9K

$101.4K

$137K

How much do kafka engineer jobs pay per year?

As of Aug 5, 2026, the average yearly pay for kafka engineer in Springfield, MA is $101,404.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,700.00 and $116,100.00 per year, depending on experience, location, and employer.

How does a Kafka engineer typically collaborate with development and operations teams?

Kafka Engineers play a key role in bridging the gap between development and operations teams. They work closely with developers to design and implement event-driven architectures using Kafka, ensuring data flows reliably between services. Simultaneously, they partner with operations teams to deploy, monitor, and maintain Kafka clusters, addressing issues like scalability, fault tolerance, and security. Effective communication and a strong understanding of both software development and infrastructure are essential for success in this collaborative environment.

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

To thrive as a Kafka Engineer, you need a strong understanding of distributed systems, proficiency in Apache Kafka, and experience with programming languages like Java or Python, often supported by a degree in computer science or a related field. Familiarity with tools such as Kafka Connect, Kafka Streams, monitoring systems (e.g., Prometheus, Grafana), and relevant certifications like Confluent Certified Developer for Apache Kafka are typically required. Problem-solving skills, effective communication, and the ability to work collaboratively make someone stand out in this position. These skills and qualities are crucial to ensure reliable data pipelines, seamless integration, and efficient troubleshooting in mission-critical, real-time data environments.

What does a Kafka engineer do?

A Kafka Engineer specializes in designing, building, and maintaining distributed data streaming systems using Apache Kafka. They are responsible for configuring Kafka clusters, ensuring data reliability and scalability, and integrating Kafka with other systems. Kafka Engineers also monitor system performance, troubleshoot issues, and optimize data pipelines to support real-time data processing needs. Their work is essential for organizations that rely on high-throughput, low-latency data streaming for applications such as analytics, event sourcing, and microservices architectures.

What is the difference between Kafka Engineer vs Data Engineer?

AspectKafka EngineerData Engineer
Required CredentialsCertifications in Kafka, cloud platforms, programming languagesCertifications in data tools, cloud, SQL, programming
Work EnvironmentFocus on Kafka setup, streaming data, real-time processingBroader data pipeline, storage, and processing tasks
Employer & Industry UsageTech companies, data-driven organizations using KafkaVarious industries managing large data systems
Common Search & ComparisonOften compared for specialization in streaming dataBroader role encompassing multiple data technologies

The Kafka Engineer specializes in designing, implementing, and maintaining Kafka-based streaming data systems, focusing on real-time data processing. In contrast, Data Engineers work on building comprehensive data pipelines, integrating various data sources, and managing storage solutions. While Kafka Engineers focus on Kafka-specific tasks, Data Engineers handle a wider range of data tools and platforms, making their roles complementary but distinct in data infrastructure teams.

How much do Kafka engineers make?

Kafka engineers in the US typically earn between $100,000 and $150,000 annually, depending on experience, location, and certifications. Senior roles or those with specialized skills in distributed systems and real-time data processing can command higher salaries. Compensation may also include benefits such as bonuses and stock options.
What are popular job titles related to Kafka Engineer jobs in Springfield, MA? For Kafka Engineer jobs in Springfield, MA, the most frequently searched job titles are:
What job categories do people searching Kafka Engineer jobs in Springfield, MA look for? The top searched job categories for Kafka Engineer jobs in Springfield, MA are:
What cities near Springfield, MA are hiring for Kafka Engineer jobs? Cities near Springfield, MA with the most Kafka Engineer job openings:
Kafka Engineer jobs near you
Infographic showing various Kafka Engineer job openings in Springfield, MA as of July 2026, with employment types broken down into 91% Full Time, 6% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $101,404 per year, or $48.8 per hour.

DATA Engineer

Teamware Solutions

East Hartford, CT • On-site

$113K - $136K/yr

Other

Posted 7 days ago

Job description

 
 

Must be Local only within 40 Miles area

Relocation will not work

 
 
Look insurance domain highly preferred
 
 

Job Description:

11 Years exp 

We are looking for a Senior Data Engineer to design, build, and optimize scalable data pipelines and warehouse solutions that power business-critical analytics. You will work closely with data architects, analysts, and business stakeholders to deliver robust data products on modern lakehouse platforms.
Key Responsibilities
  • Design and develop end-to-end data pipelines using Apache Spark and Databricks, following medallion (Bronze/Silver/Gold) architecture patterns
  • Build and maintain large-scale SQL-based data warehouses, including dimensional models, star/Client schemas, and performance-tuned queries
  • Lead data ingestion from diverse sources (RDBMS, APIs, flat files, streaming) into centralized platforms with strong data quality controls
  • Implement and enforce Unity Catalog governance standards — data lineage, access controls, tagging, and cataloging
  • Optimize Spark jobs for performance, cost efficiency, and reliability at scale
  • Collaborate with architects to define standards for data modeling, pipeline design, and naming conventions
  • Mentor junior engineers and conduct code reviews to uphold engineering best practices
  • Partner with business analysts and data consumers to translate requirements into scalable data solutions
  • Proactively identify and resolve data quality, latency, and pipeline reliability issues
Required Skills & Qualifications
  • 10+ years of hands-on experience in data engineering
  • Strong expertise in Apache Spark (PySpark / Scala) and Databricks platform
  • Deep proficiency in SQL — query optimization, window functions, complex transformations, stored procedures
  • Solid experience with data warehousing concepts — normalization, SCD types, fact/dimension modeling
  • Experience with Client Lake or similar open table formats (Apache Iceberg, Hudi)
  • Hands-on with orchestration tools such as Apache Airflow, Databricks Workflows, or Azure Data Factory
  • Familiarity with version control (Git) and CI/CD practices for data pipelines
  • Strong understanding of data governance — lineage, cataloging, data quality frameworks
  • Excellent problem-solving skills and ability to work independently in a client-facing environment
Good to Have
  • Experience with dbt (data build tool) for transformation layer development
  • Exposure to cloud platforms — AWS
  • Knowledge of streaming technologies (Kafka, Event Hubs)
  • Familiarity with Great Expectations or other data quality frameworks

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