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Senior Big Data Software Engineer

Remote in Spain
Data Software Engineering
relocation

Do you have a software engineering background and strong knowledge of Big Data? Are you an open-minded professional with good English skills? If it sounds like you, this could be the perfect opportunity to join EPAM as a Senior Big Data Engineer.

EPAM is shaping the digital future for Fortune 1000 companies, building complex solutions using modern technologies. We are looking for a Senior Big Data Engineer with an open-minded personality who can join our friendly environment and become a core contributor to our team of experts.

Responsibilities
  • Develop and implement innovative analytical solutions using Cloud Native, Big Data, and NoSQL related technologies
  • Develop and implement Cloud/On-Premise/Hybrid solutions using best in the class data frameworks
  • Work with product and engineering teams to understand requirements, evaluate new features and architecture to help drive decisions
  • Build collaborative partnerships with architects, technical leads and key individuals within other functional groups
  • Perform detailed analysis of business problems and technical environments and use this in designing quality technical solution
  • Actively participate in code review and test solutions to ensure it meets best practice specifications
  • Build and foster a high performance engineering culture, mentor team members and provide team with the tools and motivation
  • Write project documentation
Requirements
  • Coding experience with one of the following programming languages: Python/Java/Scala
  • Experience with Linux OS: configure services and write basic shell scripts, understanding of network fundamentals
  • Good knowledge of SQL and relational algebra
  • Advanced experience in software development with Data technologies (e.g. administration, configuration management, monitoring, debugging and performance tuning)
  • Engineering experience and practice in Data Management, Data Storage, Data Visualization, Disaster Recovery, Integration, Operation, Security
  • Experience building data ingestion pipelines, Data Warehouse or Database architecture
  • Experience with data modeling; hands-on development experience with modern Big Data components
  • Cloud: experience in designing, deploying and administering scalable, available and fault tolerant systems
  • Good understanding of CI/CD principles and best practices
  • Analytical approach to problem; excellent interpersonal, mentoring and communication skills
  • Data-oriented personality and possessing compliance awareness, such as PI, GDPR, HIPAA
  • Motivated, independent, efficient and able work under pressure with a solid sense for setting priorities
  • Ability to work in a fast-paced (startup like) agile development environment
  • Experience in high load and IoT Data Platform architectures and infrastructures
  • Vast experience with Containers and Resource Management systems: Docker and Kubernetes
  • Experience in direct customer communications
  • Solid skills in infrastructure troubleshooting, support and practical experience in performance tuning and optimization, bottleneck problem analysis
  • Experienced in different business domains
  • English proficiency
  • Advanced understanding of distributed computing principles
Technologies
  • Python/Java/Scala/Kotlin and SQL
  • Cloud-Native stack: Databricks, Azure DataFactory, AWS Glue, AWS EMR, Athena, GCP DataProc, GCP DataFlow
  • Big Data stack: Spark Core, Spark SQL, Spark ML, Kafka, Kafka Connect, Airflow, Nifi, Streamset
  • NoSQL: CosmosDB, DynamoDB, Cassandra, HBase; MongoDB
  • Queues and Stream processing: Kafka Streams; Flink; Spark Streaming
  • Data Visualization: Tableau, PowerBI, Looker
  • Operation: Cluster operation, Cluster planning
  • Elasticsearch/ELK
  • Solid Cloud experience with one of the leading cloud providers (AWS/Azure/GCP): Storage; Compute; Networking; Identity and Security; NoSQL; RDBMS and Cubes; Big Data Processing; Queues and Stream Processing; Serverless; Data Analysis and Visualization; ML as a service (SageMaker; Tensorflow)
  • Enterprise Design Patterns (Secure Inversion of Control etc)
  • Development Methods (TDD, BDD, DDD)
  • Version Control Systems (Git)
  • Testing: Component/ Integration Testing, Unit testing (JUnit)
  • Deep understanding of SQL queries, joins, stored procedures, relational schemas, and SQL optimization
  • Experience in various messaging systems, such as Kafka, RabbitMQ, Event Hub, Pub/Sub
  • Rest, Thrift, GRPC
  • Build Systems: Maven, SBT, Ant, Gradle
  • Docker, Kubernetes
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