Key skills
Agentic AIAirflow AWSAmazon DynamoDBAmazon EMRAmazon GlueAmazon LambdaAmazon S3Amazon SNSAmazon SQSAmazon Step FunctionsAWS QuickSightTableauGrafanaJavaScript ES6PythonRole-Based Access Control (RBAC)ReactTypeScriptNode.jsCloud ComputingDevOpsMicroservicesDistributed Cloud InfrastructureBackstageLaunchDarklyGitHub ActionsAWS EC2AWS ECSAWS VPCAWS IAMAWS CloudWatchData IngestionData TransformationData Orchestration PipelinesAWS RedshiftAWS AthenaMachine Learning LifecycleInfrastructure as CodeAWS CDKCloudFormationTerraformAWS CLIReal-time Stream ProcessingComplex Event ProcessingApache FlinkAutomated Testing FrameworksLarge Language Models (LLMs)AI Orchestration ToolsAI-assisted Coding ToolsRAG ArchitecturesPrompt EngineeringTool-augmented AI SystemsJavaScriptAIMLRAGAgenticAnalyticsRedshiftAirflowReact.jsPlaywrightAWSECSEC2LambdaS3DynamoDBIAMCloudWatchSNSSQSGlueAthenaInfluxDBGitHubPerformance OptimizationCI/CDCommunicationCollaboration
About this role
Mindlance is a company seeking a Full Stack Engineer for their External Data Analytics team. The role involves designing, developing, and ensuring the reliability of enterprise analytics platforms that support mission-critical exam operations, focusing on building scalable data architectures and high-performance reporting systems.
Responsibilities:
- Develop a strong understanding of customer business processes and exam operations
- Collaborate with Lead Engineers and Solution Architects to evaluate feature requests, provide effort estimates, and support sprint planning
- Participate in peer code and design reviews to ensure quality and consistency
- Contribute to the development and scalability of enterprise analytics platforms supporting mission-critical exam operations
- Write code to implement, and maintain cloud-native data architectures, telemetry pipelines, APIs, and reporting systems
- Build secure, scalable full-stack solutions across backend services, data platforms, and front-end analytics applications
- Implement end-to-end solutions—from data ingestion and transformation to service layers and dashboards
- Apply established architectural patterns, automation practices, and observability standards
- Ensure systems meet requirements for scalability, data integrity, availability, and reliability
- Integrate monitoring, telemetry, and operational readiness into system components
- Develop and maintain automated end-to-end and UI testing frameworks using Playwright to ensure application quality and reliability
- Embed monitoring, telemetry, and operational readiness into all platform components
- Contribute to solving complex technical problems and improving system design
- Support and collaborate with team members to promote best practices in development, testing, and system design
- Continuously improve skills across cloud, data, full-stack technologies, and test automation frameworks
- Communicate technical approaches, tradeoffs, and solutions clearly to team members and stakeholders
- Promote best practices in secure system design, automation, performance optimization, and resilient engineering
- Partner with product, operations, and security teams to deliver aligned solutions
- Support exam readiness through participation in testing, monitoring, and reliability efforts
- Contribute to documentation, knowledge sharing, and continuous improvement initiatives
- Collaborate with QA and engineering teams to integrate automated into CI/CD pipelines
- Foster a culture of ownership, documentation, accountability, and continuous improvement
Requirements:
- 3+ years of experience designing, building, and supporting scalable, cloud-native applications, data pipelines, analytics platforms
- 1+ years of experience developing modern front-end applications using TypeScript and React
- Coding/scripting experience with Python, JavaScript, React.js, Node.js
- Technical knowledge of Cloud Computing, DevOps, and Microservices
- Strong knowledge and experience with distributed cloud infrastructure within AWS
- Exceptional analytical, conceptual, and problem-solving abilities
- Experience working with AWS resources such as Lambda, SNS, SQS, S3, Step Functions, EC2, ECS, VPC, IAM, CloudWatch, DynamoDB
- Excellent communication and collaboration skills with an ability to present ideas in business-friendly and user-friendly language
- Ability to prioritize and execute tasks in a high-pressure environment
- Strong hands-on experience with backend technologies such as Node.js (preferably TypeScript) and Python, building APIs and data processing systems
- Experience working with data ingestion, transformation, and orchestration pipelines for analytical and operational workloads
- Experience in building responsive, secure, and high-performance user interfaces using TypeScript, JavaScript, HTML, and CSS
- Familiarity with asynchronous programming and event-driven architectures
- Understanding of data modeling and transformation using AWS services such as Glue, Lambda, Redshift, Athena, and S3
- Familiarity with ML lifecycle concepts and tools
- Experience using Infrastructure as Code tools such as AWS CDK, CloudFormation, Terraform, or AWS CLI
- Experience with real-time stream processing and Complex Event Processing (CEP) using Apache Flink or similar technologies is a plus
- Experience with automated testing frameworks, specifically Playwright for end-to-end and UI testing
- Strong focus on scalability, data integrity, reliability, and quality engineering practices
- Good problem-solving, analytical thinking, and communication skills
- Agentic AI
- Airflow AWS
- Amazon Dynamo
- Amazon EMR
- Amazon Glue
- Amazon Lambda
- Amazon S3
- Amazon SNS SQS
- Amazon Step Functions
- AWS - Quick Suite/Tableau
- Grafana
- JavaScript ES6
- RBAC
- react
- TypeScript
- Experience with Backstage, LaunchDarkly, GitHub Actions is a plus
- Experience with monitoring and analytics tools such as Grafana, InfluxDB, or similar
- Experience with cloud data stores and query engines such as Amazon Redshift, Athena, DynamoDB, Apache Iceberg and S3-based data lakes a plus
- Understanding of data isolation, performance segmentation, and secure access in distributed systems
- Familiarity with observability and operational strategies in distributed architectures
- Experience integrating automated testing frameworks like Playwright into CI/CD pipelines
- Experience working with LLMs, agent frameworks, or AI orchestration tools
- Familiarity with agentic workflows, autonomous system
- Hands-on experience with AI-assisted coding tools (e.g., GitHub Copilot, ChatGPT, or similar) and integrating them into development workflows
- Understanding of RAG architectures, prompt engineering, and tool-augmented AI systems