Senior Data Engineer

EPAM Systems, Inc.; Brasil; Teletrabalho; BRL 200 000 - 320 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Healthcare benefits

Paid time off

Learning programs

Global career opportunities

Volunteer opportunities

Resumo da oferta

EPAM Systems, Inc. is seeking a Senior Data Engineer to lead design, development, and maintenance of data and ML pipelines on the Domino Data Lab platform. You will own end-to-end data workflows, from ingestion to delivery, and oversee compute infrastructure for secure, reliable operations.

The role emphasizes data engineering and MLOps, with collaboration across data scientists and other engineers to meet tooling requirements and improve internal processes.

Qualificações

• At least 3 years of relevant experience.
• Deep hands-on with Domino Data Lab platform and its components.
• Expert-level Python for data engineering and pipeline development.
• Strong SQL for data extraction and transformation across warehouses.
• Experience with ETL/ELT design, data ingestion, validation, and orchestration.
• Practical Kubernetes experience and cloud familiarity (AWS/GCP/Azure).
• Knowledge of CI/CD pipelines for data workflows and containerization.

Responsabilidades

• Build and sustain reliable data pipelines powering analytics and ML workloads.
• Oversee end-to-end data workflows from ingestion to delivery.
• Manage compute infrastructure for efficient, secure platform operations.
• Diagnose and resolve pipeline performance and data quality issues.
• Collaborate with data scientists and engineers on infrastructure needs.
• Promote best practices for platform usage and data workflows.

Conhecimentos

Python

SQL

Kubernetes

Docker

CI/CD

Linux Bash

Domino Platform

Data Pipelines

ETL/ELT

ML Ops

Cloud (AWS/GCP/Azure)

Formação académica

Bachelor's degree in CS/Engineering

Ferramentas

Jenkins

GitHub Actions

Airflow

Kubeflow

MLflow

Descrição da oferta de emprego

We are looking for a Senior Data Engineer to head the design, development, and upkeep of data and ML pipelines on the Domino Data Lab platform. This position centers on the data engineering and MLOps aspects of Domino, constructing dependable data pipelines, overseeing model lifecycle workflows, and keeping the platform's data and compute infrastructure running efficiently and securely. This is not a front-end or application development role.ResponsibilitiesBuild and sustain dependable data pipelines that power analytical and machine learning workloadsHandle the full lifecycle of data workflows, spanning ingestion, transformation, and deliveryManage compute infrastructure to keep platform operations efficient, secure, and dependableDiagnose and resolve issues that affect pipeline performance and data qualityWork alongside data scientists and other engineers to meet their infrastructure and tooling requirementsDefine and champion best practices around platform usage, pipeline design, and data workflow structureIntroduce automation into testing and deployment processes to boost reliability and cut down manual workKeep watch over pipeline health and get ahead of bottlenecks or failures before they escalateHelp drive continuous improvement of internal tools and processes that support data operationsRecord technical designs, workflows, and configurations to enable knowledge sharing throughout the teamRequirementsAt least 3 years of relevant experienceDeep hands-on experience with the Domino Data Lab platform, including Data Sources and Connectors, Datasets, Environments, Projects, Jobs, and Flows, with the ability to architect and troubleshoot end-to-end data pipelines and promote best practices for platform usageExpert-level command of Python as the main language for data engineering and pipeline developmentStrong SQL skills for extracting, transforming, and optimizing data across relational and warehouse systemsComfortable using R and Bash across the wider data science toolchain and for scripting automationProven experience designing, constructing, and maintaining ETL/ELT pipelines, including data ingestion, transformation, validation, and orchestrationPractical experience with Kubernetes and managed offerings such as EKS, AKS, or GKE, with the ability to deploy, debug, and fine-tune cluster workloads running data and ML jobsExperience creating, optimizing, and troubleshooting container images for data and ML workloads using DockerExperience establishing and maintaining CI/CD pipelines using tools such as Jenkins, GitLab CI, GitHub Actions, or Azure DevOps to automate testing and deployment of data pipelines and ML workflowsWorking familiarity with at least one major cloud provider, such as AWS, Azure, or GCP, with the ability to evaluate data architecture, cost, and security trade-offsExcellent English proficiency (B2 level or higher)Nice to haveExperience with Domino Nexus or hybrid/multi-cloud compute orchestrationExperience delivering ML workflows spanning training, deployment, monitoring, and retraining, with an understanding of reproducibility and versioningPractical experience with GenAI, LLMs, or agentic frameworks, including retrieval-augmented generation (RAG), from a data pipeline perspectiveFamiliarity with orchestration tools such as MLflow, Kubeflow, Airflow, or Domino FlowsKnowledge of model governance, compliance automation, or audit logging frameworksExperience working within pharma, BFSI, or public sector environmentsWe offerInternational projects with top brandsWork with global teams of highly skilled, diverse peersHealthcare benefitsEmployee financial programsPaid time off and sick leaveUpskilling, reskilling and certification coursesUnlimited access to the LinkedIn Learning library and 22,000+ coursesGlobal career opportunitiesVolunteer and community involvement opportunitiesEPAM Employee GroupsAward-winning culture recognized by Glassdoor, Newsweek and LinkedInEPAM is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, disability, protected veteran status, or any other characteristic protected by applicable law.