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Amazon Redshift Jobs in Connecticut (NOW HIRING)

Data Architect

Hartford, CT · On-site

$64.25 - $82.75/hr

Talend,PySpark,Amazon Redshift,ETL,ELT,Kafka,Apache Spark,Java,NoSQL,AWS EMR.,data pipeline,Apache NiFI,Kylo,Scripting,Power BI,Tableau,Qlik,data ingestion,wrangling,cleansing,Advanced SQL,SQL,Python ...

Design, implement, and optimize batch and real-time data processing solutions leveraging AWS Glue, Lambda, Apache Iceberg (Amazon S3 Tables), Redshift, and related cloud-native services. * Manage and ...

Amazon Redshift Database setup, maintenance and Cloudwatch. #LI-DNP #LI-DNI Compensation Pay Disclosure: Voya is committed to pay that's fair and equitable, which means comparable pay for comparable ...

Amazon Redshift information

See Connecticut salary details

$27

$54

$75

How much do amazon redshift jobs pay per hour?

As of Aug 6, 2026, the average hourly pay for amazon redshift in Connecticut is $54.27, according to ZipRecruiter salary data. Most workers in this role earn between $46.63 and $60.58 per hour, depending on experience, location, and employer.

What is the difference between Amazon Redshift vs Data Warehouse Engineer?

AspectAmazon RedshiftData Warehouse Engineer
Primary RoleCloud-based data warehousing service for analyticsDesigning, building, and maintaining data warehouses and ETL processes
Required SkillsSQL, cloud computing, data modeling, AWS servicesSQL, data modeling, ETL tools, database management
Work EnvironmentCloud platforms, AWS ecosystemOn-premises or cloud data warehouse environments
CertificationsAWS certifications, SQL knowledgeData management certifications, SQL expertise

Amazon Redshift is a cloud-based data warehousing service focused on providing scalable analytics within the AWS ecosystem. In contrast, a Data Warehouse Engineer designs and maintains data warehouses, often working with various tools and environments. While both roles require SQL and data modeling skills, Redshift specialists focus on cloud infrastructure, whereas Data Warehouse Engineers handle broader data architecture tasks across different platforms.

Is Amazon Redshift hard to learn?

Amazon Redshift is a data warehousing service that requires understanding SQL, database concepts, and data modeling. Learning it involves gaining familiarity with cloud environments, query optimization, and performance tuning, which can take time but is manageable with structured training and practice.

What are the key skills and qualifications needed to thrive as an Amazon Redshift developer, and why are they important?

To thrive as an Amazon Redshift Developer, you need strong SQL expertise, experience with data warehousing concepts, and a background in computer science or related fields. Familiarity with AWS services (especially Redshift), ETL tools, and relevant certifications like AWS Certified Data Analytics are typically required. Problem-solving, attention to detail, and effective communication are standout soft skills in this role. These skills enable efficient data pipeline development, ensure data integrity, and support collaboration for optimized analytics solutions.

What are some common challenges faced by Amazon Redshift administrators and how can they be addressed?

Amazon Redshift administrators often encounter challenges such as optimizing query performance, managing data loads, and ensuring data security. Performance tuning requires careful management of distribution styles, sort keys, and regular vacuuming to maintain efficiency. Handling large-scale data loads can be addressed by using COPY commands and leveraging parallel processing. Collaboration with data engineers and analysts is essential to understand data usage patterns and set up appropriate monitoring and alerting. Continuous learning and staying updated with AWS enhancements can help administrators proactively resolve issues and optimize the data warehouse environment.

What is Amazon Redshift?

Amazon Redshift is a fully managed, cloud-based data warehouse service provided by Amazon Web Services (AWS). It is designed to handle large-scale data analytics and can process petabytes of structured and semi-structured data quickly and efficiently. Redshift uses SQL to query data and integrates seamlessly with various business intelligence tools, making it a popular choice for organizations looking to analyze big data. Its architecture is based on columnar storage and massively parallel processing (MPP), which enables high performance and scalability.
What job categories do people searching Amazon Redshift jobs in Connecticut look for? The top searched job categories for Amazon Redshift jobs in Connecticut are:
Infographic showing various Amazon Redshift job openings in Connecticut as of August 2026, with employment types broken down into 86% Full Time, 7% Part Time, 3% Temporary, and 4% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $112,879 per year, or $54.3 per hour.

$64.25 - $82.75/hr

Full-time

Re-posted 3 days ago


Job description

Overview:
Position: Data Architect
Location: Hartford, CT (Remote right now)
Duration: 12+Months
Mandatory Skills: Talend, PySpark, Redshift
Job Description
Responsibilities:
Translating data and technology requirements into our ETL / ELT architecture.
Develop real-time and batch data ingestion and stream-analytic solutions leveraging technologies such as Kafka, Apache Spark, Java, NoSQL DBs, AWS EMR.
Develop data driven solutions utilizing current and next generation technologies to meet evolving business needs.
Develop custom cloud-based data pipeline.
Provide support for deployed data applications and analytical models by identifying data problems and guiding issue resolution with partner data engineers and source data providers.
Provide subject matter expertise in the analysis, preparation of specifications and plans for the development of data processes.
Qualifications:
Strong experience in data ingestion, gathering, wrangling and cleansing tools such as Apache NiFI, Kylo, Scripting, Power BI, Tableau and/or Qlik
Experience with data modeling, data architecture design and leveraging large-scale data ingest from complex data sources
Experience building and optimizing 'big data' data pipelines, architectures and data sets.
Advanced SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
Strong knowledge of analysis tools such as Python, R, Spark or SAS, Shell scripting, R/Spark on Hadoop or Cassandra preferred.
Strong knowledge of data pipelining software e.g., Talend, Informatica
Skills:
Talend,PySpark,Amazon Redshift,ETL,ELT,Kafka,Apache Spark,Java,NoSQL,AWS EMR.,data pipeline,Apache NiFI,Kylo,Scripting,Power BI,Tableau,Qlik,data ingestion,wrangling,cleansing,Advanced SQL,SQL,Python,Hadoop,Cassandra,R/Spark,Informatica