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Senior Data DevOps Engineer
- Pay
- Pay not listed
- Work setting
Remote — work setting source
Work setup in the employer’s posting: TELECOMMUTE
From the employer’s posting- Employment
- Not stated
What you’ll work on
Full postingSupport data engineering and machine learning teams with production-ready infrastructure
Automate build, deployment, and operational processes
Ensure reliability, performance, security, and observability of systems
Troubleshoot production issues and collaborate with development teams
From the employer’s posting
Support data engineering and machine learning teams with production-ready infrastructure
Automate build, deployment, and operational processes
Ensure reliability, performance, security, and observability of systems
Troubleshoot production issues and collaborate with development teams
What you’ll bring
All qualificationsCore experience
- At least 4 years in DevOps, cloud or data platform roles
- Bachelor's degree in Computer Science or equivalent practical experience
- Strong Linux/Unix administration, networking and performance tuning
- Experience designing and operating production-grade systems
- Python, at least 2 years hands-on
Qualification wording
Minimum 4 years of professional experience in DevOps / Cloud / Data Platform roles
Bachelor’s degree in Computer Science or equivalent practical experience
Strong Linux/Unix administration, networking, troubleshooting, performance tuning, and optimization skills
Experience designing and operating production-grade systems
Python (minimum 2 years hands-on experience)
Tools in this posting
- Bash
- Python
- AWS
- Azure
- BigQuery
- Databricks
- Datadog
- Delta Lake
- Docker
- Elasticsearch
- GCP
- Grafana
- Hadoop
- Kafka
- Kubernetes
- MLflow
- Prefect
- Redshift
- S3
- SageMaker
- Spark
- Terraform
- Airflow
Source — Tool mentions in context
We are seeking a Senior Data DevOps Engineer to design, build and operate robust cloud-based data platforms, supporting data engineering and machine learning teams with scalable, production-ready infrastructure. Technologies we are interested in... Cloud Platforms · AWS: EC2, S3, IAM, VPC; Glue, Redshift, EMR, Kinesis; SageMaker · Azure: VM, Storage, RBAC, Networking; Synapse, Data Factory, Event Hubs; Azure ML · GCP (basic): BigQuery, Pub/Sub, Dataflow Infrastructure, Containers & Automation · Infrastructure as Code: Terraform (AWS & Azure), Terragrunt, ARM / Bicep · Containers & orchestration: Docker, Kubernetes (EKS / AKS), Helm · Configuration management: Ansible, Chef, Puppet or similar · CI/CD: Jenkins, TeamCity, Bamboo, GoCD or similar Data, Streaming & ML Platforms · Apache Spark, Apache Kafka · Delta Lake / Lakehouse architectures · Databricks · Workflow orchestration: Airflow or Prefect · MLOps & ML platforms: MLflow, Feature Stores (Feast), Model Serving (KFServing, TorchServe) Big Data, Monitoring & Security · Hadoop: HDFS, YARN; Cloudera or Hortonworks; Ambari, Cloudera Manager; Hive, HUE, Spark; Hadoop Security (intermediate) · Monitoring & observability: Prometheus, Grafana, Datadog, Zabbix, Nagios · Search & analytics: Elasticsearch (intermediate) · Security best practices and authentication/authorization: LDAP, Kerberos, SAML Programming · Python (minimum 2 years hands-on experience) · One scripting language: Bash, Perl, or Groovy Responsibilities Design, build, and operate highly available, scalable cloud-based data platforms Support data engineering and machine learning teams with production-ready infrastructure Automate build, deployment, and operational processes Ensure reliability, performance, security, and observability of systems Troubleshoot production issues and collaborate with development teams Create and maintain technical documentation, procedures, and knowledge transfers Requirements Bachelor’s degree in Computer Science or equivalent practical experience Minimum 4 years of professional experience in DevOps / Cloud / Data Platform roles Strong Linux/Unix administration, networking, troubleshooting, performance tuning, and optimization skills Experience designing and operating production-grade systems Strong analytical, problem-solving, and communication skills Ability to visualize and explain architectures English B2 or higher
Posting record
Report an errorActively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 1, 20262 days ago
- Recorded sightings
- 4
- Last seen by us
- Nov 4, 2026
- Employer says posted
- Sep 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
EPAM Systems is hiring
656 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordYour next step
Check the employer’s posting for the current role and application details.
Already applied? Track this application
Has EPAM Systems posted this job before?
Yes. We’ve followed 5 other Senior Data DevOps Engineer jobs there since November 2026. All 5 are still up.
Large employers often post one title for several teams, so these can be separate openings.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
We are seeking a Senior Data DevOps Engineer to design, build and operate robust cloud-based data platforms, supporting data engineering and machine learning teams with scalable, production-ready infrastructure. Technologies we are interested in... Cloud Platforms · AWS: EC2, S3, IAM, VPC; Glue, Redshift, EMR, Kinesis; SageMaker · Azure: VM, Storage, RBAC, Networking; Synapse, Data Factory, Event Hubs; Azure ML · GCP (basic): BigQuery, Pub/Sub, Dataflow Infrastructure, Containers & Automation · Infrastructure as Code: Terraform (AWS & Azure), Terragrunt, ARM / Bicep · Containers & orchestration: Docker, Kubernetes (EKS / AKS), Helm · Configuration management: Ansible, Chef, Puppet or similar · CI/CD: Jenkins, TeamCity, Bamboo, GoCD or similar Data, Streaming & ML Platforms · Apache Spark, Apache Kafka · Delta Lake / Lakehouse architectures · Databricks · Workflow orchestration: Airflow or Prefect · MLOps & ML platforms: MLflow, Feature Stores (Feast), Model Serving (KFServing, TorchServe) Big Data, Monitoring & Security · Hadoop: HDFS, YARN; Cloudera or Hortonworks; Ambari, Cloudera Manager; Hive, HUE, Spark; Hadoop Security (intermediate) · Monitoring & observability: Prometheus, Grafana, Datadog, Zabbix, Nagios · Search & analytics: Elasticsearch (intermediate) · Security best practices and authentication/authorization: LDAP, Kerberos, SAML Programming · Python (minimum 2 years hands-on experience) · One scripting language: Bash, Perl, or Groovy Responsibilities Design, build, and operate highly available, scalable cloud-based data platforms Support data engineering and machine learning teams with production-ready infrastructure Automate build, deployment, and operational processes Ensure reliability, performance, security, and observability of systems Troubleshoot production issues and collaborate with development teams Create and maintain technical documentation, procedures, and knowledge transfers Requirements Bachelor’s degree in Computer Science or equivalent practical experience Minimum 4 years of professional experience in DevOps / Cloud / Data Platform roles Strong Linux/Unix administration, networking, troubleshooting, performance tuning, and optimization skills Experience designing and operating production-grade systems Strong analytical, problem-solving, and communication skills Ability to visualize and explain architectures English B2 or higher
Source details
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- Location & working pattern
Hungary
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- Work authorization
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