CSI Analytics - Data Engineering Associate

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CSI Analytics – Data Engineering Associate

Job Details

 Position Title  CSI Analytics – Data Engineer – Associate

Job Purpose

CSI Analytics goal is to solve complex business and operational problems and enable informed decision making through scalable, secure, and high performance data platforms. The Data Engineering Associate will work within the Operational Excellence – CSI Analytics team to design, build, and maintain resilient data engineering solutions that support enterprise analytics, reporting, and AI driven use cases.

As a Data Engineering Associate, the role combines strong cloud data engineering expertise with disciplined delivery and quality practices to ensure reliable, well governed, and reusable data products. The associate will be responsible for building ingestion pipelines, curated data layers, and analytical data models using Azure native and Microsoft Fabric technologies while adhering to CSI Analytics standards, governance, and platform best practices.

The Data Engineering Associate will be supported by the CSI Data Engineering Lead; however, the candidate is expected to be highly self driven, capable of independently solving complex data challenges, and proactive in proposing scalable and future ready solutions.

Key Role and Responsibilities

 This Data Engineering Associate will be responsible for delivering scalable, secure, and high quality data engineering solutions to meet exceptional client and internal stakeholder expectations. Standard work includes but is not limited to:

Data Engineering & Platform Development   

Design, develop, and maintain end to end data pipelines using Azure Data Factory, Databricks, and Microsoft Fabric to ingest data from diverse structured and unstructured sources.

•  Knowledge to implement and manage Medallion Architecture (Bronze, Silver, Gold layers) ensuring data quality, reusability, and performance optimization across analytics use cases.
• Develop efficient and well governed analytical data models to support reporting, advanced analytics, and downstream AI initiatives.
• Ensure adherence to CSI Analytics engineering standards, coding best practices, and documentation guidelines.
• Optimize data pipelines for performance, scalability, and cost efficiency within Azure and Fabric environments.
• Extremely proficient in SQL development

Metadata, Governance & Quality Management 

•  Implement data quality checks, validation rules, and reconciliation processes to ensure accuracy, completeness, and consistency of data assets.
• Ensure compliance with EY data security, privacy, and regulatory standards, including access controls and audit requirements.

Qualifications, Experience and Skills

Qualifications

• Bachelor’s degree in computer science or a related discipline

Experience

• A minimum of 2–3 years of experience working in Data Engineering, Data Platform, or Enterprise Analytics roles
• Strong hands on experience building cloud scale data solutions on Microsoft Azure

Data Engineering and Cloud Expertise

• Demonstrates strong expertise in Azure Data Factory, Databricks, and Microsoft Fabric for enterprise grade data engineering solutions.
• Applies end to end data engineering skills covering ingestion, transformation, curation, and analytical modelling.
• Implements Medallion Architecture based data platforms aligned to analytics and reporting needs.
• Develops robust data models optimized for performance, scalability, and consumption by BI and analytics tools.

Data Mining & Optimization

• Connects seamlessly with multiple data sources to develop optimized, high-performance data pipelines.
• Applies advanced data optimization techniques and demonstrates proficiency in data cleansing and formatting using SQL, Python, or other analytical tools.

Technical Skills/Competencies

• Strong expertise in Azure Data Factory, Databricks, and Microsoft Fabric
• Advanced SQL and data modeling skills
• Strong analytical, troubleshooting, and problem-solving skills
• Good communication and stakeholder collaboration skills
• Ability to manage ambiguity, shifting priorities, and complex data landscapes

Behavioral Competencies

• Teamwork
• Integrity
• Empathy & care
•  Ownership
• Accountability         
•   Analytical thinking and problem solving
• Coherent communication
•  Time management and organization
•  Extreme attention to detail

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