Senior Data Integration Engineer

at  EPAM Systems Inc

We are currently looking for a Senior Data Integration Engineer to join our Prague office. PROJECT

REQUIREMENTS

• At least 3 years of relevant development experience and practice with data management, data storage, data modeling, data analytics, data migration, and database design
• Practical hands-on experience in developing Data Solutions in at least one major public Cloud environment (AWS, Azure, GCP)
• Practical knowledge of leading cloud data warehousing solutions (e.g. Redshift, Azure Synapse Analytics, Google BigQuery, Snowflake, etc.)
• Production coding experience in one of the data-oriented programming languages
• Solid background in developing Data Analytics & Visualization, Data Integration or DBA & Cloud Migration Solutions
• Experienced and highly self-motivated professional with outstanding analytical and problem-solving skills
• Play the role of a Key Developer and a Designer or a Team Lead of 2-5 engineers and ensure that delivered solutions meet business requirements and expectations
• Able to read and understand project and requirement documentation; able to create design and technical documentation including high-quality documentation of his/her code
• Experienced in working with modern Agile developing methodologies and tools
• Able to work closely with customers and other stakeholders
• Advanced knowledge of Data Integration tools (Azure Data Factory, AWS Glue, GCP Dataflow, Talend, Informatica, Pentaho, Apache NiFi, KNIME, SSIS, etc.)
• Advanced knowledge of Relational Databases (SQL optimization, Relations, Stored Procedures, Transactions, Isolation Levels, Security)
• Practical hands-on experience of development of Data Solutions in Cloud environments (AWS, Azure, GCP) - designing, implementing, deploying, and monitoring scalable and fault-tolerant data solutions
• Solid understanding of core cloud technologies and approaches. Awareness of niche and case-specific cloud services
• Expected ability to troubleshoot the outages of average complexity, identify and trace performance issues
• Pattern-driven solutioning, choosing the best for particular business requirements and technical constraints
• Advanced knowledge of Data Security (Row-level data security, audit, etc.)
• Production experience of one of the data-oriented programming languages: SQL, Python, SparkSQL, PySpark, R, Bash
• Production projects experience in Data Management, Data Storage, Data Analytics, Data Visualization, Data Integration, MDM (for MDM profiles), Disaster Recovery, Availability, Operation, Security, etc
• Experience with data modeling (OLAP, OLTP, ETL and DWH / Data Lake /Delta Lake/ Data Mesh methodologies. Inman vs Kimbal, Staging areas, SCD and other dimension types)
• Good understanding of Online and streaming integrations, micro-batching, Understanding of CDC methods and delta extracts
• General understanding of Housekeeping processes (archiving, purging, retention policies, hot/cold data, etc.)
• Good understanding of CI/CD principles and best practices. Understanding of concepts of “Canary release”, Blue-Green, Red-Black deployment models
• Data-oriented focus and possessing compliance awareness, such as PI, GDPR, HIPAA
• Experience in direct customer communications
• Experienced in different business domains
• English proficiency

• Design and implement Data Integration solutions, model databases, and contribute to building data platforms using classic Data technologies and tools (Databases, ETL/ELT technology & tools, MDM tools, etc.) as well as implementing modern Cloud or Hybrid data solutions
• Work with product and engineering teams to understand data product requirements, evaluate new features and architecture to help and drive decisions
• Build collaborative partnerships with architects and key individuals within other functional groups
• Perform detailed analysis of business problems and technical environments and use this in designing high-quality technical solutions
• Actively participate in code review and testing of solutions to ensure it meets specification and quality requirements
• Build and foster a high-performance engineering culture, supervise junior/middle team members and provide them technical leadership
• Write project documentation
• Be self-managing, implement functionality without supervision, test his/her work thoroughly using test cases, and/or supervise less experienced colleagues