Lead Cloud & DevOps Engineer, Blend
The starting pay range for this role is $65/hr - $75/hr
Business performance data & analytics
Be an early applicant
Business performance data & analytics
501-1000 employees
Be an early applicant
The starting pay range for this role is $65/hr - $75/hr
501-1000 employees
Company mission
To help advance our understanding of our customers and business performance.
Role
Who you are
- We are looking for an experienced Senior Cloud & DevOps Engineer to support the build and production readiness of a foundational AWS data platform for a large telecommunications client
- The ideal candidate will have strong expertise in AWS-native architecture, infrastructure-as-code (Terraform), release engineering, observability, and secure platform operations in regulated environments
- Strong hands-on experience with CI/CD tooling and release automation
- Experience with infrastructure-as-code using Terraform or similar tools
- Hands-on experience deploying and operating cloud-native workloads in AWS, including services such as AWS Glue, Amazon S3, Amazon Redshift, Amazon ECS/EKS, AWS Lambda, IAM, and VPC networking
- Experience with Databricks and/or Snowflake deployments in AWS environments
- Strong understanding of containerisation, serverless architectures, managed compute services, and environment promotion strategies
- Experience with observability tooling covering logging, monitoring, alerting, and service health
- Knowledge of security best practices including IAM, RBAC, secrets management, encryption, and policy-driven access control
- Experience supporting production-grade data platforms in enterprise environments, ideally in regulated sectors with compliance requirements such as PIPEDA or equivalent
- Familiarity with Git-based workflows and collaborative engineering practices
- Strong troubleshooting, communication, and stakeholder management skills
Desirable
- Experience with AWS data and analytics services including AWS Glue, Amazon Redshift, Amazon Athena, AWS Lake Formation, Amazon EMR, and Amazon S3 data lake architectures
- Familiarity with medallion/lakehouse architectures using Databricks or Snowflake on AWS
- Experience with CI/CD pipelines using GitHub Actions, Jenkins, GitLab CI, or AWS CodePipeline/CodeBuild
- Experience with ECS or EKS-based deployments and container orchestration in AWS
- Experience implementing observability and data quality monitoring for ingestion pipelines and SLA-driven orchestration workflows
- Understanding of Canadian data privacy requirements (PIPEDA) and how they translate into platform controls such as PII tagging, RBAC design, encryption, audit logging, and data governance
- Experience supporting service transition into managed support models
- Exposure to QA automation and non-functional testing in cloud-native systems
What the job involves
- This is an HOURLY/TEMPORARY POSITION that could become permanent over time
- This role will focus on provisioning and operating the core AWS infrastructure, including data ingestion and orchestration services, data lake and analytics platforms, and establishing the CI/CD pipelines, environment management, monitoring, and operational controls needed to take the platform through Development, Test, and Production
- This person will work closely with Data Engineers, BI Consultants, and Governance leads to ensure the platform is deployable, scalable, secure, and aligned with enterprise compliance and security standards
- Design and implement AWS cloud infrastructure and deployment patterns for the data platform, including multi-account AWS Organizations strategy, IAM design, networking, naming conventions, and tagging standards
- Build and maintain CI/CD pipelines to support repeatable, controlled releases across Development, Test, and Production environments
- Provision and configure AWS infrastructure as code (Terraform), including services such as AWS Glue, Amazon S3, Amazon Redshift, VPC networking, VPN/Direct Connect connectivity, Route 53, security groups, and firewall controls to connect on-premises source systems
- Configure Git-based integration and deployment workflows for platforms such as Databricks or Snowflake to enforce version-controlled deployments
- Support deployment of backend services, orchestration components, data services, APIs, and front-end applications
- Enable monitoring, logging, alerting, and telemetry using services such as Amazon CloudWatch, AWS CloudTrail, AWS Config, and observability platforms like Datadog
- Define and implement operational controls for reliability, performance, scalability, backup/recovery, and incident response
- Implement and enforce secure access patterns using AWS IAM, IAM Identity Center (AWS SSO), AWS Secrets Manager, AWS KMS, and policy-driven access controls, including row-level and column-level security requirements where applicable
- Ensure the solution aligns with architecture, security, governance, and service transition requirements
- Support non-functional testing, release readiness, and path-to-production activities
- Produce comprehensive operational runbooks, platform documentation, and a full IaC handover package enabling the client’s internal IT team to take ownership of platform operations at programme close
- Support cost management, network performance tuning, and security hardening of the AWS platform; contribute to FinOps reporting and disaster recovery planning
Our take
As large enterprises race to digitize everything from supply chains to customer service, they're drowning in data, but not always insights. So, that's where Blend comes it, helping businesses turn messy, underused data into something genuinely useful, applying advanced analytics and AI to drive smarter decisions rather than just prettier dashboards.
Made up of data scientists and engineers, Blend works behind the scenes to make machine learning actually function in the real world. Fro, from AI integration to data governance and MLOps. Essentially, it helps big companies get more value out of the information they already have, improving efficiency and making data a competitive advantage rather than a compliance headache.
Backed by a 2022 Growth Equity investment, Blend has expanded through smart acquisitions, including FutureproofAI, which broadened its AI capabilities and client reach, and Montevideo Labs, strengthening its footprint in Latin America.
Freddie
Company Specialist at Welcome to the Jungle
Insights
Company
Company HQ
Town Center, Columbia, MD
Leadership
Patrick Hennessy
(Co-Founder & CEO)Previously a Managing Director at Whitegate Capital Partners, an Advisor to the CEO at Merkle and a Vice President at Cornwell Data.
Tim Berry
(Co-Founder)Previously a President of Merkle Europe, a Senior Director of Rapp Collins Worldwide and a Senior Manager at AT&T.
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