Remote AWS Native Developer: Data Pipelines & ML Ops

TechDigital Group; United States; Remote; USD 80,000 - 130,000; Full time

Job summary

An innovative firm is seeking a skilled data engineer to design and maintain scalable data pipelines in AWS. This role involves developing Python applications to handle large datasets and collaborating with data scientists to deploy machine learning models. You will also manage cloud infrastructure using Terraform and ensure the smooth operation of data workflows. If you are passionate about cloud technologies and data engineering, this is a fantastic opportunity to make a significant impact in a forward-thinking environment.

Qualifications

• Strong expertise in Python and AWS services for data management.
• Experience with Terraform for cloud infrastructure management.

Responsibilities

• Design and maintain scalable data pipelines for AWS cloud environments.
• Collaborate with data scientists to manage ML models and data workflows.

Skills

Python

AWS (DMS, Glue, Lambda, Athena, Opensearch, DynamoDB, DocumentDB)

Git

SQL and NoSQL

Docker

Kubernetes

Terraform

Job description

JD:
• Install, configure, and administer MongoDB deployments (self-managed and/or managed service) across non-prod and prod environments.
• Design and operate high availability and disaster recovery solutions (replica sets, multi-region architectures) to meet RPO/RTO targets.
• Plan, execute, and validate backup/restore strategies (snapshot and logical backups), including regular recovery testing and audit-ready evidence.
• Monitor cluster health and performance (CPU/memory, disk, connections, replication lag, locks/WT cache behavior, query latency) and implement proactive alerting.
• Perform performance tuning: index reviews, slow query analysis, query plan reviews, cache and resource sizing, and storage optimization.
• Manage security controls: authentication/authorization (RBAC), TLS, encryption at rest, key management integrations, network controls, and auditing.
• Execute patching and version upgrades with minimal downtime, including release notes review, compatibility checks, and rollback plans.
• Implement and maintain automation for provisioning and configuration management (scripting, IaC, CI/CD hooks) and standardize cluster build patterns.
• Support sharding operations where applicable (chunk balancing, shard key guidance, resharding planning) in partnership with architects and developers.
• Troubleshoot incidents and lead database operational response: triage, mitigation, root-cause analysis, and post-incident remediation actions.
• Capacity planning and cost optimization: forecast growth, scale resources, and right-size clusters based on workload trends.
• Maintain documentation, runbooks, and operational SOPs; provide guidance to application teams on MongoDB operational best practices.

Top Skills:
• Should be bale to maintain the db for scale in production
• All standard DBA work and work with developers on fix validation
• To identify issues before it occurs at production