Data Analyst

Sutherland

About The Position

This role focuses on Data Engineering & Fabric Development, Data Modeling, SQL Development, Python Development, and Analytics & Reporting. The company specializes in Artificial Intelligence, Automation, Cloud Engineering, and Advanced Analytics, working with global brands to drive digital transformation through market-leading technologies and business process excellence. The core expertise lies in Digital Engineering, which powers innovation and scalable business transformation. The company has a strong patent portfolio, particularly in AI, and leverages advanced products and platforms to optimize operations, reinvent experiences, and pioneer new solutions through an 'as-a-service' model. They provide new keys for businesses, people, and customers, engineering digital outcomes with proven strategies and agile execution.

Requirements

3-7 years of experience in Data Analytics, Data Engineering, or Business Intelligence.
Minimum 2 years of hands-on experience with Microsoft Fabric or Azure-based analytics platforms.
Proven experience building: Fact Tables, Dimension Tables, Data Pipelines, Power BI datasets.
Experience with Microsoft Azure Data Services.
Experience with Delta Tables and Apache Spark.
Familiarity with CI/CD and Git-based development.
Understanding of data governance and lineage concepts.

Nice To Haves

Microsoft Fabric Certification preferred: DP-600, DP-700

Responsibilities

Design and develop data pipelines using Microsoft Fabric Data Factory.
Create and maintain Lakehouse and Warehouse solutions within Microsoft Fabric.
Implement and manage Bronze, Silver, and Gold Layer architectures.
Develop scalable ETL/ELT pipelines for ingesting and transforming data from multiple sources.
Monitor pipeline performance and troubleshoot data quality issues.
Design and develop Fact Tables and Dimension Tables following dimensional modeling principles.
Create and maintain Star Schema and Snowflake Schema data models.
Define surrogate keys, business keys, and Slowly Changing Dimensions (SCD) where required.
Optimize data models for reporting and analytics performance.
Write complex SQL queries for data extraction, transformation, and validation.
Build views, stored procedures, and reusable query frameworks.
Perform query optimization and performance tuning.
Develop Python-based data transformation and validation scripts.
Use libraries such as: Pandas, NumPy, PySpark, Requests.
Automate data quality checks and reconciliation processes.
Partner with business stakeholders to gather reporting and analytics requirements.
Develop datasets optimized for Power BI reporting.
Support creation of KPIs, metrics, and business data definitions.
Ensure data governance and consistency across analytical solutions.