Job Summary:

The Data Engineer will be primarily responsible for the data integration (ETL) between our operational data sources and central data-lake and creating specific data-marts according to data analytics team’s needs.

Job Responsibilities:

 Management of data inflow

• Create and maintain optimal data pipeline architecture; adopt new technologies to improve existing frameworks of data flow and monitoring
• Assemble large, complex data sets that meet functional / non-functional business requirements
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and ‘big data’ technologies; take necessary steps to implement necessary changes in the IT infrastructure such as MDM tool acquisition, data lake design, cloud solutions implementation in coordination with IT and technology coordinator
• Create data tools for analytics and data science team members that assist them in building models by automating and simplifying data preparation
• Translate customer data strategy into actionable data integration plans and execute these plans
• Maintain 360 degree view of customer, enhance the customer datamarts by continuously integrating new sources of data

Data cleansing and unification

• Create automated data anomaly detection systems and constant tracking of its performance
• Process, cleanse, and verify integrity of data used for analysis; active use of built-in data quality dashboard on CDP and coordination of corrective actions
• Develop algorithms to de-duplicate and export customer data from multiple BUs to ensure data unification
• Ensure continuous unification of customer records and associated profile and transactional data

Candidate Requirements:

• Bachelor’s degree in Computer Science, Computer Engineering, Mathematics, or related field
• Understanding of data modeling principles
• 5+ years of significant configuration and data management experience; comfortable handling and manipulating data, with demonstrated experience in a data-intensive setting
• Professional working experience on ETL Process for customer and transactional data
• Professional project expertise preferably on Talend, Matillion or any equivalent ETL Tools
• Expert level knowledge of RDBMS Scripting Language (MS SQL, Oracle, Postgres, etc..)
• Experience working in a cloud environment preferably AWS
• Experience identifying data anomalies or imperfections
• Experience of data structures and schemas, data preparation, cleansing and unification
• Possess the ability to train others – pass on knowledge within the organization