Data Architect I - T

Role Description

Job Description: Data Architect

SummaryWe are seeking an experienced and highly motivated Azure Data Architect to join a Data & Analytics team. The ideal candidate will be a hands-on technical leader responsible for architecting, developing, implementing, and managing scalable, robust, and secure data solutions on the Microsoft Azure platform. This role involves leading a team of data engineers, setting technical direction, ensuring the quality and efficiency of data pipelines, and collaborating closely with data scientists, analysts, and business stakeholders to meet data requirements.

Key Responsibilities Design, architect, and implement end-to-end data solutions on Azure, including data ingestion, transformation, storage (lakes/warehouses), and serving layers.

Provide technical guidance to a team of Azure Data Engineers.

Oversee and actively participate in the development, testing, and deployment of robust ETL/ELT pipelines using key Azure services.

Establish and enforce data engineering best practices, coding standards, data quality checks, and monitoring frameworks.

Ensure data solutions are optimized for performance, cost, scalability, security, and reliability.

Collaborate effectively with data scientists, analysts, and business stakeholders to understand requirements and deliver effective data solutions.

Manage, monitor, and troubleshoot Azure data platform components and pipelines.

Contribute to the strategic technical roadmap for the data platform.

Experience1. Minimum 10+ years of overall experience in data engineering roles.

• Minimum 5+ years of hands-on experience designing, implementing, and managing data solutions specifically on the Microsoft Azure cloud platform.
  
  

Education1. Bachelor's degree in Computer Science, Engineering, Information Technology, or a related quantitative field (or equivalent practical experience).

Technical Skills Core Azure Data Services: Deep expertise in Azure Data Factory (ADF), Azure Synapse Analytics (SQL Pools, Spark Pools), Azure Databricks, Azure Data Lake Storage (ADLS Gen2).

Data Processing & Programming: Strong proficiency with Spark (using PySpark or Scala) and expert-level SQL skills. Proficiency in Python is highly desired.

Data Architecture & Modeling: Solid understanding of data warehousing principles (e.g., Kimball), dimensional modeling, ETL/ELT patterns, and data lake design.

Databases: Experience with relational databases (e.g., Azure SQL Database) and familiarity with NoSQL concepts/databases is beneficial.

Version Control: Proficiency with Git for code management.

Data Visualisation: Experience with Power BI.

Skills

data architecture,azure databricks,azure synapse analytics,azure data factory,data warehousing,dimensional modeling,data lake design,sql,azure sql database,pyspark,scala,spark,azure data lake storage