data engineer (etl developer)

yayınlanma
şimdi başvur

iş ilanı detay

yayınlanma
lokasyon
kozyatağı, ıstanbul (anadolu)
sektör
IT & Telekomünikasyon
referans numarası
5064

iş tanımı

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.

nitelikler

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
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