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Remote Aws Redshift Jobs in Minnesota (NOW HIRING)

HHAeXchange

Platform Engineer

Minneapolis, MN · Remote

Position is remote for candidates located within the NYC, DC-Baltimore, and Minneapolis metro areas ... Manage and optimize AWS environments including ECS, Lambda, S3, RDS, Redshift, API Gateway, and ...

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Remote Aws Redshift information

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

To thrive as a Remote AWS Redshift Engineer, you need a strong background in data warehousing, SQL, and cloud architecture, typically supported by experience with AWS services and sometimes certifications like AWS Certified Data Analytics. Familiarity with tools such as AWS Redshift, S3, Glue, and ETL solutions is crucial for managing and optimizing large-scale data environments. Excellent problem-solving, communication, and self-motivation are key soft skills for collaborating remotely and addressing complex data challenges. These skills ensure effective data management, optimized performance, and successful collaboration in distributed cloud-based teams.

What are some common challenges faced by remote AWS Redshift engineers, and how can they be addressed?

Remote AWS Redshift engineers often face challenges such as coordinating with distributed teams, maintaining secure data access, and troubleshooting data pipeline issues without on-site support. Effective communication tools, clear documentation, and regular virtual check-ins help address collaboration hurdles. Leveraging AWS security best practices and automated monitoring tools can streamline issue detection and resolution, ensuring data integrity and system performance even while working remotely.

What is the difference between Remote Aws Redshift vs Remote Data Warehouse Engineer?

AspectRemote Aws RedshiftRemote Data Warehouse Engineer
Required CredentialsAWS certifications, SQL knowledgeData warehousing certifications, SQL, cloud platform knowledge
Work EnvironmentCloud-based, data analytics teamsData infrastructure teams, cloud or on-premises environments
Industry UsageData analytics, BI, cloud servicesData integration, analytics, enterprise data solutions
Search & Comparison IntentFocus on AWS Redshift-specific skillsBroader data warehouse skills including multiple platforms

Remote Aws Redshift specialists focus on managing and optimizing AWS Redshift data warehouses, often requiring AWS certifications and SQL expertise. Remote Data Warehouse Engineers have a broader scope, working with various data warehouse platforms and integrating data solutions across different environments. While both roles involve data management and analytics, Redshift roles are more cloud-specific, whereas Data Warehouse Engineers may work across multiple cloud or on-premises systems.

What is a Remote AWS Redshift job?

A Remote AWS Redshift job involves working with Amazon Web Services (AWS) Redshift, a cloud-based data warehouse service, from a remote location. Professionals in this role are responsible for designing, implementing, and maintaining Redshift clusters, optimizing data storage and queries, and ensuring data security and performance. Common tasks include ETL (Extract, Transform, Load) processes, managing large datasets, and integrating Redshift with other AWS services. These roles are suitable for data engineers, analysts, and database administrators who can work effectively outside a traditional office setting. Remote AWS Redshift jobs typically require strong SQL skills, experience with cloud platforms, and knowledge of data warehousing concepts.
What are popular job titles related to Remote Aws Redshift jobs in Minnesota? For Remote Aws Redshift jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Remote Aws Redshift jobs in Minnesota look for? The top searched job categories for Remote Aws Redshift jobs in Minnesota are:
Remote Aws Redshift jobs near you
Platform Engineer

Platform Engineer

HHAeXchange

Minneapolis, MN • Remote

Full-time

Medical, Retirement, PTO

Re-posted yesterday

Job description

HHAeXchange is the leading technology platform for home and community-based care. Founded in 2008, HHAeXchange was born out of an idea to create a fully comprehensive end-to-end homecare solution to help people who are aging or have disabilities thrive in their homes and communities. Our employees are passionate about transforming the healthcare space by building the only homecare ecosystem that fully connects patients, personal care providers, managed care organizations, and states.

HHAeXchange is seeking a Platform Engineer to join our Data & AI Engineering team. Reporting to the Director of Analytics, this role sits at the intersection of platform reliability and delivery automation - ensuring the infrastructure that powers our AI platform, data pipelines, and internal applications is stable, scalable, and continuously improving.

This is a hands-on engineering role embedded within a team building Layer 1 of HHAeXchange's AI Platform - the core machinery that enables AI-powered capabilities across the organization. The engineer will own the reliability and deployment lifecycle of that infrastructure, working closely with AI Platform Engineers and Data & AI Engineers to operationalize everything we build on AWS.

As our AI platform matures and internal tooling expands, this role becomes the connective tissue between development velocity and production stability - ensuring that what gets built gets shipped reliably, monitored proactively, and scaled confidently.

To perform this job successfully, an individual must be able to perform each essential job duty satisfactorily with or without reasonable accommodation. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Position is remote for candidates located within the NYC, DC-Baltimore, and Minneapolis metro areas.

Essential Job Duties

Platform Reliability (SRE)

  • Own availability, latency, and performance targets for AI platform services and data infrastructure running on AWS
  • Design and implement monitoring, alerting, and observability frameworks across the platform stack
  • Lead incident response, root cause analysis, and post-mortem processes for platform-level outages or degradations
  • Define and track SLOs/SLAs for core platform primitives including RAG pipelines, agent orchestration services, and model access layers
  • Proactively identify reliability risks and drive engineering improvements before they become production issues
  • Build and maintain runbooks, disaster recovery procedures, and operational documentation

DevOps & Delivery Automation

  • Design, build, and maintain CI/CD pipelines for AI platform components, data pipelines, and internal applications
  • Own infrastructure-as-code (IaC) practices across the team using tools such as Terraform or AWS CDK
  • Manage and optimize AWS environments including ECS, Lambda, S3, RDS, Redshift, API Gateway, and related services
  • Implement and enforce security, compliance, and cost optimization best practices across AWS infrastructure
  • Automate deployment, scaling, and configuration management to reduce manual operational overhead
  • Partner with AI Platform Engineers to containerize and operationalize AI services and agent frameworks
  • Support Data & AI Engineers with environment management, access controls, and deployment tooling for Polaris and data pipeline infrastructure

Cross-Team Enablement

  • Serve as the operational backbone for the AI platform team - ensuring engineers can ship and iterate quickly without being blocked by infrastructure concerns
  • Contribute to our "factory model" vision by making deployment and reliability a repeatable, scalable capability rather than an ad hoc function
Other Job Duties
  • Other duties as assigned by supervisor or HHAeXchange leader.
Travel Requirements
  • Travel up to 10%, including overnight travel
Required Education, Experience, Certifications and Skills
  • 3+ years of professional experience in a DevOps, SRE, or platform engineering role
  • Hands-on AWS experience required - AgentCore, Bedrock, ECS, Lambda, S3, RDS, Redshift, CloudWatch, IAM, VPC, and related services
  • Experience with infrastructure-as-code tools such as Terraform or AWS CDK
  • Strong CI/CD experience with tools such as GitHub Actions
  • Experience with containerization and orchestration (Docker, ECS, or Kubernetes)
  • Familiarity with AI/ML infrastructure patterns - model serving, vector databases, pipeline orchestration (strongly preferred)
  • Experience with observability and monitoring tooling (Datadog, CloudWatch)
  • Prior experience in a SaaS environment
  • Strong verbal and written communication skills with ability to collaborate across technical and non-technical stakeholders
  • Self-starter with a proactive approach to identifying and resolving infrastructure risk before it impacts delivery
  • Willingness to explore and adopt AI tools responsibly to enhance productivity and innovation in your role.
The base salary range for this US-based, full-time, and exempt position is $110,000-120,000/yr, not including variable compensation. An employee's exact starting salary will be based on various factors including but not limited to experience, education, training, merit, location, and the ability to exemplify the HHAeXchange core values.
 
This is a benefits-eligible position. HHAeXchange offers competitive health plans, paid time-off, company paid holidays, 401K retirement program with a Company elected match, including other company sponsored programs.
 
HHAeXchange is an equal-opportunity employer. The Company offers employment opportunities to all applicants and employees without regard to race, color, religion, national origin, sex, sexual orientation, gender identity or expression, age, disability, medical condition, marital status, veteran status, citizenship, genetic information, hairstyles, or any other status protected by local or federal law.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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