data engineer (etl developer) in kozyatağı

posted
job type
permanent
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job details

posted
location
kozyatağı, istanbul (asia)
job category
IT & Telecommunication
job type
permanent
reference number
4792

job description

We are looking for “Data Engineer” for our customer in insurance sector.

This person will be responsible for the data architecture, modeling, design and development of data warehouse solutions, and can understand business/system/data challenges translate them into requirements/solutions.

Performing data integration for data warehouse applications

Manage the underlying data processing and architecture as it flows from the data sources through ETL processing to staging areas and through ingestion into the back-end databases that drive the platforms.

Understanding of user data requirements, analysis of source data and designing data models to support analytic reporting.

Perform Logical and physical database design for schemas required in support of Business Intelligence tools such as Oracle OBIEE and Microsoft Power BI

Recommend and implement data validation and data quality enhancements for the organization. Identify data errors, risks, and inefficiencies and improve process and system functionality to increase system controls, minimize data errors, and process data accurately and efficiently.

Ensure the designs and solutions comply with the Aegon Global Standards and Blueprints.

qualification

At least 5 years’ experience on a similar role in

Experience in developing solution architecture guidelines, policies and processes and guiding design teams.

Expertise with data modelling, database design, and data management techniques and models including:

Data Warehouse / Data Marts

Data mining

ETL

Big Data / Data Lake

Business Intelligence

Conceptual, logical and physical data modelling.

OLAP design and implementation

Familiarity with object modelling in UML

Knowledge of an enterprise-scale SDLC.

Experience in Oracle DB, Oracle DWH, Oracle ODI, Oracle OBIEE and Power BI

Worked with Analytics tools such as Oracle BI Power BI

Broad understanding on architectures of Hadoop, AWS or Azure data lakes

Understanding of machine learning techniques and algorithms

Knowledge about common data science toolkits, such as Python R

Strong verbal and written communication skills