Data Manager

Role Overview

We are looking for an experienced Data Manager to lead the design, development, and management of enterprise-scale data platforms. The role will be responsible for managing data architecture, data engineering initiatives, cloud data platforms, ETL/ELT pipelines, and distributed data processing solutions using Microsoft Azure technologies.

Key Responsibilities

• Lead the design and implementation of scalable data architecture, data lakes, data warehouses, and enterprise data platforms.
• Manage end-to-end data engineering initiatives covering data ingestion, transformation, processing, storage, and consumption.
• Design and optimize ETL/ELT pipelines for batch and distributed data processing.
• Lead data platform development using Azure Data Factory, Azure Databricks, ADLS, and Azure Synapse Analytics.
• Define data integration and processing strategies across structured and unstructured data sources.
• Ensure data platforms are scalable, reliable, secure, and optimized for performance and cost.
• Manage and mentor data engineering teams and provide technical guidance on data solutions.
• Collaborate with business stakeholders, architects, and technology teams to understand requirements and translate them into scalable data solutions.
• Monitor data pipelines and troubleshoot performance, data quality, and operational issues.
• Establish best practices around data governance, data quality, security, and platform standards.
• Drive modernization and migration of existing data platforms to Azure cloud-based solutions.
• Review technical designs and ensure adherence to architecture and engineering standards.

Required Technical Skills

Big Data & Data Engineering

• Big Data technologies
• Distributed data processing
• ETL / ELT
• Data ingestion and integration
• Data Lakes
• Data Warehouses
• Data Architecture
• Data Modelling
• Batch and large-scale data processing

Microsoft Azure

• Azure Data Factory (ADF)
• Azure Databricks
• Azure Data Lake Storage (ADLS)
• Azure Synapse Analytics

Programming & Database

• Strong SQL
• Python / PySpark
• Relational and distributed databases
• Data pipeline optimization

Leadership & Management

• Lead and mentor Data Engineers and technical teams.
• Plan resources and manage delivery timelines.
• Review architecture, technical designs, and data engineering solutions.
• Coordinate with stakeholders across business and technology teams.
• Ensure successful delivery of data projects within agreed timelines and quality standards.

Preferred Experience

• Experience in Azure cloud data platform implementation.
• Enterprise-scale data migration and modernization.
• Experience designing Data Lake / Data Warehouse / Lakehouse solutions.
• Strong understanding of distributed data processing.
• Experience managing data engineering teams.
• Exposure to data governance, security, and data quality frameworks.