Data Engineering & Analytics AssociateBroughton Group • Atlanta, Georgia, United States
Data Engineering & Analytics Associate
Broughton Group
- Atlanta, Georgia, United States
- Atlanta, Georgia, United States
Über
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.
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Sprachkenntnisse
- English
Hinweis für Nutzer
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