Data Engineering & Analytics Associate

Data Engineering & Analytics Associate Location: Atlanta, GA (Hybrid - Banking Client Environment) Industry: Banking & Financial Services About the Opportunity (Why this role is different) At CirrusLabs, we are building a next-generation Data Modernization team for a leading banking client. This is not just a "data role" - this is a front-row seat to how modern banks are transforming into AI-driven enterprises. As part of our Rising Stars Program, you will: Work on Azure Databricks Lakehouse platform Help migrate legacy systems into cloud-native data architecture Build pipelines that power AI, analytics, fraud detection, and customer insights Contribute to systems that enable real-time business decisions at scale What You’ll Work On (Real Banking Data Modernization Projects) Cloud Data Modernization Support migration from legacy systems to Azure + Databricks Lakehouse Work with structured, semi-structured, and streaming data Help build scalable, cloud-native data platforms Data Engineering & Pipelines Build and optimize ETL/ELT pipelines using: Python / PySpark SQL Databricks Workflows Work with Delta Lake architecture Data Analytics & AI Enablement Enable data for: Customer insights Fraud detection Risk analytics Operational reporting Support ML/AI use cases using curated datasets Data Governance & Quality Ensure data accuracy, consistency, and lineage Work with governance frameworks (e.g., Unity Catalog concepts) Support regulatory-grade data reporting Data Products & Business Insights Build datasets powering dashboards (Power BI/Tableau) Support creation of data products used by business teams Help transform raw data into actionable insights What We’re Looking For (Fresh Graduate Profile) Education: Bachelor's or Master’s in: Computer Science Data Science / Analytics Information Systems Engineering (any discipline with data exposure) Core Skills (Must Have Potential): Strong fundamentals in: SQL Python (or willingness to learn) Understanding of: Data structures Basic ETL concepts Analytical thinking and problem-solving mindset Bonus (Nice to Have): Exposure to: PySpark / Spark Cloud platforms (Azure preferred) Data visualization (Power BI / Tableau) Knowledge of: Data warehousing concepts APIs and data integration What You Will Learn (Career Acceleration Path) This program is designed to fast-track you into: Data Engineer Senior Data Engineer Data Architect AI/Data Leader You will gain hands‑on experience in: Azure Data Ecosystem (ADF, Databricks, Storage) Lakehouse Architecture (Delta Lake) Data Engineering at enterprise scale AI/ML data pipelines Financial services data systems Why This Role Matters Banks today are not just financial institutions - they are data companies.

Every transaction, fraud signal, and customer interaction depends on data. AI and analytics rely on clean, scalable, real‑time data pipelines. Data platforms directly impact revenue, risk, and customer experience.

Without modern data systems, banks cannot compete or innovate. #J-18808-Ljbffr