Data Engineer

Data Engineer

Overview of Job Function

• Are you excited about DWH, Big data and Analytics? Would you love the opportunity to design and build data pipeline technologies? Does solving complex problems motivate you? If yes, we are looking for you!
• NLB Digit is looking for a Senior/Medior Data Engineer to join our Data management team and help build the technologies used to drive our advanced Analytics capabilities. You will be part of a team responsible for the vision and architecture of scalable data pipeline solutions utilizing various data movement and transformation technologies.

Summary of Responsibilities

• Participates in the process of development and improvement of the centralized Data warehouse.
• Contribute, as part of a team, in designing, testing, and implementing sophisticated data pipeline technologies to extract and transform data from source systems
• Participates in the data management process with aim of raising the level of data quality in terms of timeliness, relevance, and reliability, for the needs of business analysis and reporting.
• Perform data-modelling on target systems to store data and support analytic querying
• Design development, maintenance and testing of ETL processes and validation rules.
• Actively participates with other development, data science teams, and business users to gather and document requirements and defining reporting methodologies.
• Work in Agile methodology and participate in design and review meetings
• Follow best practices for the software development life-cycle including coding standards, reviews, source management, build and testing

Position Requirements

• 3+ years of experience as a Data Engineer or in a similar role working with large data sets and ETL processes
• 5+ years of industry experience in software development
• Degree in Computer Science, Engineering, Mathematics, or a related field
• Knowledge and practical use of a wide variety of RDBMS technologies such as SQL Server, DB2, MySQL or Oracle
• Strong SQL experience with an emphasis on analytic queries and performance
• Use of Data flow and transformation tools such as IBM Data Stage or Microsoft SSIS
• Experience with Python or Java
• Use of large shared data stores such as Hadoop File System
• Thorough and practical use of various Data Warehouse data schemas (Snowflake, Star, OLAP cube)
• Excellent written and verbal English language communication skills