We are seeking a Senior Backend & Data Engineer to join its SaaS Data Platform team.
This role offers a unique opportunity to design and build large-scale, high-performance data platforms and backend services that power our cloud-based products.
You will own features end to end-from architecture and design through development and production deployment-while working closely with Data Science, Machine Learning, DevOps, and Product teams.
What Youll Do:
Design, develop, and maintain scalable, secure data platforms and backend services on AWS.
Build batch and streaming ETL/ELT pipelines using Spark, Glue, Athena, Iceberg, Lambda, and EKS.
Develop backend components and data-processing workflows in a cloud-native environment.
Optimize performance, reliability, and observability of data pipelines and backend services.
Collaborate with ML, backend, DevOps, and product teams to deliver data-powered solutions.
Drive best practices, code quality, and technical excellence within the team.
Ensure security, compliance, and auditability using AWS best practices (IAM, encryption, auditing).
Tech Stack:
AWS Services: S3, Lambda, Glue, Step Functions, Kinesis, Athena, EMR, Airflow, Iceberg, EKS, SNS/SQS, EventBridge
Languages: Python (Node.js/TypeScript a plus)
Data & Processing: batch & streaming pipelines, distributed computing, serverless architectures, big data workflows
Tooling: CI/CD, GitHub, IaC (Terraform/CDK/SAM), containerized environments, Kubernetes
Observability: CloudWatch, Splunk, Grafana, Datadog
Key Responsibilities:
Design, develop, and maintain scalable, secure backend services and data platforms on AWS
Build and operate batch and streaming ETL/ELT pipelines using Spark, Glue, Athena, Iceberg, Lambda, and EKS
Develop backend components and data processing workflows in a cloud-native environment
Optimize performance, reliability, and observability of data pipelines and backend services
Collaborate with ML, backend, DevOps, and product teams to deliver data-driven solutions
Lead best practices in code quality, architecture, and technical excellence
Ensure security, compliance, and auditability using AWS best practices (IAM, encryption, auditing)
Requirements: 8+ years of experience in Data Engineering and/or Backend Development in AWS-based, cloud-native environments
Strong hands-on experience writing Spark jobs (PySpark) and running workloads on EMR and/or Glue
Proven ability to design and implement scalable backend services and data pipelines
Deep understanding of data modeling, data quality, pipeline optimization, and distributed systems
Experience with Infrastructure as Code and automated deployment of data infrastructure
Strong debugging, testing, and performance-tuning skills in agile environments
High level of ownership, curiosity, and problem-solving mindset.
Nice to Have:
AWS certifications (Solutions Architect, Data Engineer)
Experience with ML pipelines or AI-driven analytics
Familiarity with data governance, self-service data platforms, or data mesh architectures
Experience with PostgreSQL, DynamoDB, MongoDB
Experience building or consuming high-scale APIs
Background in multi-threaded or distributed system development
Domain experience in cybersecurity, law enforcement, or other regulated industries.
This position is open to all candidates.