Senior Big Data Software Engineer

Description Do you have a sofware engineering background and strong knowledge in 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. Our teams work in highly agile working environments for Fortune clients, following XP practices and best CI/CD practices. We are looking for a Senior Big Data Engineer with open‑minded personality, who can join our friendly environment and become a core contributor to our team of experts. What You’ll Do 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 What You Have 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 We Offer WORK & LIFE BALANCE. Enjoy more of your personal time with flexible & remote work options, 24 working days of annual leave and paid time off for numerous public holidays CONTINUOUS LEARNING CULTURE. Develop your hard & soft skills with internal training and mentorship opportunities, sponsored professional certification, and access to 18,+ LinkedIn courses CLEAR & DIFFERENT CAREER PATHS. Grow in engineering or managerial direction to become a People Manager, in-depth technical specialist, Solution Architect, or Project/Delivery Manager GLOBAL RELOCATION OPPORTUNITIES. EPAM has presence in more than 50 countries globally. Explore opportunities to relocate to a new country, and EPAM will provide relocation support for you and your family COMPETITIVE BENEFITS. Benefit from a competitive salary, private health insurance, employee stock purchase plan, special discount programs, plus, internal wellbeing programs to take your career to the next level STRONG PROFESSIONAL COMMUNITY. Join a global EPAM community of highly skilled experts and connect with them to solve challenges, exchange ideas, share expertise and make friends About EPAM EPAM is a leading digital transformation services and product engineering company with over 53, EPAMers in more than 55 countries and regions . Since , our multidisciplinary teams have been helping make the future real for our clients and communities around the world. In , we opened an office in Spain that quickly grew to over 1, EPAMers distributed between the offices in Málaga and Madrid as well as remotely across the country . Here you will collaborate with multinational teams, contribute to numerous innovative projects, and have an opportunity to learn and grow continuously Additional #DA_SP #J-18808-Ljbffr