101 to 125 of 176 Remote Amazon Redshift Jobs

The Data Architect is responsible for designing, building, and managing the data warehouse’s data architecture, ensuring it is scalable, secure, and optimized for performance. This position plays a crucial role in shaping our data ...

Proficient in data analysis and reporting, with experience in tools like Tableau, Power BI, or similar * Strong knowledge of AWS data services, such as Redshift, Glue, or Athena * Ability to translate complex datasets into easily understandable insights * Familiarity with SQL and data querying techniques * Experience working in collaborative environments ...

built your career on AWS this is one where that depth actually gets used. • AWS across the board, including S3, Glue, Redshift, Lake Formation and Kinesis • Databricks and Snowflake running on top of AWS • Spark and distributed processing frameworks for large-scale data • Streaming technologies such as Kinesis ...

Haves Direct experience selling customer data platforms, data integration, developer tools, cloud infrastructure, or AI infrastructure. Familiarity with technologies such as Snowflake, Databricks, BigQuery, Redshift, Kafka, dbt, or related modern data platforms. Experience selling infrastructure or consumption‐based software. Prior experience at a company navigating a major product ...

will work across a range of AWS technologies, supporting infrastructure hosted on services including ASGs, ECS, RDS Aurora MySQL, MSK, ElastiCache, S3, and Redshift Spectrum. This is an exciting opportunity to join a team during a period of technical growth, with platform upgrades and ongoing discussions around architecture, technology … infrastructure-focused role Experience working at scale Deep hands-on experience with AWS, ideally with 5+ years' experience using: -ASG -ALB -ECS -CloudFront -Redshift -Lambda -ElastiCache -RDS (Aurora) -Control Tower The Desirables Previous experience with affiliate tracking, data integrations, or similar environments Experience delivering near-zero downtime database migrations ...

Company Description We’re Checkout.com. You might not know our name, but companies like eBay, Spotify, Klarna, Uber, and Sony do, because we’re behind many of the digital experiences you use every day. We ...

Company DescriptionWe’reCheckout.com. You might not know our name, but companies like eBay, Spotify, Klarna, Uber, and Sony do, because we’re behind many of the digital experiences you use every day. We are where ...

insights. Responsibilities: Design & build scalable data pipelines of AWS Ingest, transform and model data from multiple source systems Work with S3, Glue, Lambda, Athena, Redshift and related AWS Services Support CI/CD and infrastructure as a code Requirements: Must have strong, commercial AWS (contract) Data Engineering experience Must … solid knowledge of data warehousing and modelling Experience with Airflow and infrastructure as a code (Terraform, CloudFormation) would be beneficial Must have experience with Redshift Nice to have: Experience with dbt/lake formation One or more AWS Certifications #J-18808-Ljbffr ...

insights. Responsibilities: - Design & build scalable data pipelines of AWS - Ingest, transform and model data from multiple source systems - Work with S3, Glue, Lambda, Athena, Redshift and related AWS Services - Support CI/CD and infrastructure as a code Requirements: - Must have strong, commercial AWS (contract) Data Engineering experience - Must … solid knowledge of data warehousing and modelling - Experience with Airflow and infrastructure as a code (Terraform, CloudFormation) would be beneficial - Must have experience with Redshift Nice to have: - Experience with dbt/lake formation - One or more AWS Certifications Applications are now open! - Reach out to Adam Akhtar ...

C#/.NET fundamentals and software development principles. Ability to work effectively in a fast-paced, dynamic environment. Familiarity with AWS technologies (EC2, RedShift, DynamoDB, Firehose, Kinesis) a plus. Exposure to digital advertising technologies (e.g., AdMob) a plus. Passion for building high-quality systems and collaborating with peers ...

C#/.NET fundamentals and software development principles. Ability to work effectively in a fast-paced, dynamic environment. Familiarity with AWS technologies (EC2, RedShift, DynamoDB, Firehose, Kinesis) a plus. Exposure to digital advertising technologies (e.g., AdMob) a plus. Passion for building high-quality systems and collaborating with peers ...

active SC clearance for this role.Desirable skills- Public sector or regulated industry experience (government, healthcare orsimilar)- Experience with modern data warehouse and lakehouse ecosystems (Redshift, Snowflake, Databricks, BigQuery, Synapse)- Familiarity with SQL and Python or Java- Experience with MLOps and Infrastructure as Code (Terraform, CloudFormation etc.) for data, analytics … approaches to IT and infrastructuredelivery- Cloud platform architecture certification, with a data or AI specialism beneficial- Certification in modern data warehouse/AI ecosystems (Redshift, Snowflake, Databricks etc.)- Experience using AI or Agentic techniques in application of the role through GitHub CoPilot, Claude Code, or equivalentBenefitsAlong with a great ...

active SC clearance for this role.Desirable skills- Public sector or regulated industry experience (government, healthcare orsimilar)- Experience with modern data warehouse and lakehouse ecosystems (Redshift, Snowflake, Databricks, BigQuery, Synapse)- Familiarity with SQL and Python or Java- Experience with MLOps and Infrastructure as Code (Terraform, CloudFormation etc.) for data, analytics … approaches to IT and infrastructuredelivery- Cloud platform architecture certification, with a data or AI specialism beneficial- Certification in modern data warehouse/AI ecosystems (Redshift, Snowflake, Databricks etc.)- Experience using AI or Agentic techniques in application of the role through GitHub CoPilot, Claude Code, or equivalentBenefitsAlong with a great ...

well Data engineering & the platform Build and maintain ingestion and transformation pipelines across our stack. We use a modern data stack, such as AWS, Redshift, and Airflow Write production‐quality Python for extraction, transformation, and automation tasks that fall outside dbt’s remit Help us modernise: we’re actively … stack and expect you to challenge and improve it, not just operate it Warehouse cost & performance Own the performance and cost profile of our Redshift warehouse — you should be able to read a query plan, choose sensible sort and distribution keys, and design incremental models without being asked Spot ...

target data architecture and modernization roadmap Assess Teradata workloads schemas ETL processes stored procedures and dependencies Design migration solutions to AWS services such as Redshift S3 Glue EMR Aurora and Lakehouse platforms Lead migration planning wave management cutover rollback and data validation activities Architect data integration CDC replication … Data Architecture Data Engineering with 8 years of Teradata and cloud migration experience Strong expertise in Teradata Vantage BTEQ TPT Fast Load Multiload AWS Redshift S3 Glue EMR Aurora DMS Data Warehousing Data Lakes Lakehouse Architectures ETLELT Modernization and SQL Migration Terraform GitHub GitLab CICD DevSecOps Experience delivering largescale ...

around it. Data & SQL depth : Fluent in analytical SQL and data modeling - you've built and debugged multi-stage warehouse pipelines (ours run on Redshift) and reconciled messy source data into something trustworthy. You've worked across the major database paradigms - relational, key-value/document, and search … where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. You don't need to have trained them. ...

around it. Data & SQL depth : Fluent in analytical SQL and data modeling - you've built and debugged multi-stage warehouse pipelines (ours run on Redshift) and reconciled messy source data into something trustworthy. You've worked across the major database paradigms - relational, key-value/document, and search … where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. You don't need to have trained them. ...

around it. Data & SQL depth : Fluent in analytical SQL and data modeling - you've built and debugged multi-stage warehouse pipelines (ours run on Redshift) and reconciled messy source data into something trustworthy. You've worked across the major database paradigms - relational, key-value/document, and search … where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. You don't need to have trained them. ...

around it. Data & SQL depth : Fluent in analytical SQL and data modeling - you've built and debugged multi-stage warehouse pipelines (ours run on Redshift) and reconciled messy source data into something trustworthy. You've worked across the major database paradigms - relational, key-value/document, and search … where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. You don't need to have trained them. ...

around it. Data & SQL depth : Fluent in analytical SQL and data modeling - you've built and debugged multi-stage warehouse pipelines (ours run on Redshift) and reconciled messy source data into something trustworthy. You've worked across the major database paradigms - relational, key-value/document, and search … where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. You don't need to have trained them. ...

around it. Data & SQL depth : Fluent in analytical SQL and data modeling - you've built and debugged multi-stage warehouse pipelines (ours run on Redshift) and reconciled messy source data into something trustworthy. You've worked across the major database paradigms - relational, key-value/document, and search … where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. You don't need to have trained them. ...

around it. Data & SQL depth : Fluent in analytical SQL and data modeling - you've built and debugged multi-stage warehouse pipelines (ours run on Redshift) and reconciled messy source data into something trustworthy. You've worked across the major database paradigms - relational, key-value/document, and search … where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. You don't need to have trained them. ...

around it. Data & SQL depth : Fluent in analytical SQL and data modeling - you've built and debugged multi-stage warehouse pipelines (ours run on Redshift) and reconciled messy source data into something trustworthy. You've worked across the major database paradigms - relational, key-value/document, and search … where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. You don't need to have trained them. ...

around it. Data & SQL depth : Fluent in analytical SQL and data modeling - you've built and debugged multi-stage warehouse pipelines (ours run on Redshift) and reconciled messy source data into something trustworthy. You've worked across the major database paradigms - relational, key-value/document, and search … where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. You don't need to have trained them. ...

around it. Data & SQL depth : Fluent in analytical SQL and data modeling - you've built and debugged multi-stage warehouse pipelines (ours run on Redshift) and reconciled messy source data into something trustworthy. You've worked across the major database paradigms - relational, key-value/document, and search … where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. You don't need to have trained them. ...