Senior Data Platform Engineer (Databricks)

Remote in Spain

Data Software Engineering

We are seeking an experienced Senior Data Platform Engineer with a profound expertise in Databricks and multi-cloud environments to join EPAM.

In this role, you'll engineer scalable, high-performance data solutions that unlock the full potential of data for our Fortune 1000 clients. If you thrive in building data platforms from scratch and driving innovations across cloud platforms, this opportunity at EPAM could be perfect for you.

Responsibilities

Architect and deploy robust, scalable, and secure data platforms using Databricks, ensuring optimal performance and security
Create cloud-agnostic solutions across AWS, Azure, and GCP to ensure flexibility and system resilience
Design and implement end-to-end data pipelines integrating data lakes, warehouses, and streaming frameworks
Leverage Databricks SQL, Delta Lake, MLflow, and advanced Spark optimization techniques for data interaction and performance enhancements
Collaborate with cross-functional teams to implement and maintain workflows based on Databricks following best practices
Develop and maintain CI/CD pipelines specifically tailored for seamless data platform deployment and testing
Set up and manage monitoring, logging, and alerting frameworks to ensure infrastructure health and operational excellence
Optimize compute and storage resources to achieve cost-efficiency without compromising on performance
Troubleshoot and resolve issues related to Databricks and Spark performance
Mentor team members on cluster management, job optimization, and resource allocation within Databricks environments
Ensure adherence to compliance standards and maintain platform security
Drive adoption of advanced capabilities in Databricks like Photon and Graviton instances for improved efficiency
Regularly update and refine existing architectures to meet changing business and technology needs

Requirements

Extensive experience with Databricks, Apache Spark, and distributed data processing systems
Strong programming skills in Python, Scala, and SQL
Proficiency in AWS (specifically S3, IAM, Lambda), Azure, or GCP focusing on data engineering services
Expertise in data architecture principles, including data lakes, lakehouses, and ETL workflows
Hands-on experience with CI/CD tools and infrastructure as code practices (Terraform, CloudFormation preferred)
Familiarity with monitoring and observability frameworks suitable for large-scale data environments
Strong analytical and problem-solving skills
Excellent communication and teamwork abilities
Ability to self-manage and operate effectively in a dynamic environment

Nice to have

Certifications in Databricks, AWS, Azure, or GCP
Knowledge of Kubernetes and containerized deployments for data pipelines
Experience with real-time data streaming frameworks and governance tools

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