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Senior Manager - Data Engineer.MGN Pak - Digital Data Platforms.MIT - PAKCO at Mashreq Careers

İzmir, Aegean Region, Turkey -

Full Time

Start Date

Immediate

Expiry Date

13 May, 26

Salary

0.0

Posted On

12 Feb, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Big Data, Hadoop, Data Lake, Data Mesh Architectures, Azure Cloud, Microsoft SQL Server, Unix, Apache Spark, Pyspark, Hive, Azure Data Bricks, ADF, Data Management, Data Architecture, Data Governance, Python

Industry

Banking

Description

Data & Analytics Driven Organization: One Data Analytics & AI Business Unit drive the vision to transform the Bank into a Data Driven Organization (DDO) using latest tools and technologies in Data space. Wholesale & Ops Data team is a stream within One Data Organization driving this agenda for Wholesale & Ops Banking function. Data Engineer will design and maintain data pipelines of real-time and batch, creates data strategy, data architecture, best practices and who can lead the organization in making strategical improvements in the data engineering solutions. This role requires to have a knowledge of core system, payment systems, digital journeys, marketing systems, risk and compliance systems which are very data intensive systems across UAE, Egypt, Pakistan and other IBG regions etc. Our core function spans multiple platforms like Enterprise Data Lake, Azure Data Lake, Business Intelligence, Advanced Analytics and Realtime Streaming platforms. The work involves developing new requirements in both on-premises and cloud data lake’s estimating the efforts, designing an effective solution, data architecture and management, change release management, resource management, handling the deliverables across the business groups in the Bank. Also, handling critical applications that influence bank’s management decision making process, regulatory reporting (which can influence financial/non-financial penalties) and operational reporting.

Responsibilities

The Data Engineer will design and maintain real-time and batch data pipelines, establish data strategy, architecture, and best practices to lead strategic improvements in data engineering solutions. This involves developing new requirements across on-premises and cloud data lakes, managing resources, handling deliverables, and overseeing critical applications influencing decision-making and regulatory reporting.