Data Engineering & Analytics Associate

Data Engineering & Analytics AssociateOur vision is to become the world's most sought-after niche digital transformation company that helps customers realize value through innovation. Our mission is to co-create success with our customers, partners, and community. Our goal is to enable employees to dream, grow, and make things happen. We are committed to excellence. We are a dependable partner organization that delivers on commitments. We strive to maintain integrity with our employees and customers. Every action we take is driven by value. The core of who we are is through our well-knit teams and employees. You are the core of a values-driven organization. You have an entrepreneurial spirit. You enjoy working as a part of well-knit teams. You value the team over the individual. You welcome diversity at work and within the greater community. You aren't afraid to take risks. You appreciate a growth path with your leadership team that journeys how you can grow inside and outside of the organization. You thrive upon continuing education programs that your company sponsors to strengthen your skills and for you to become a thought leader ahead of the industry curve. You are excited about creating change because your skills can help the greater good of every customer, industry, and community.Role: Data Engineering & Analytics AssociateLocation: Atlanta, GA (Hybrid – Banking Client Environment)Industry: Banking & Financial ServicesAbout 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 platformHelp migrate legacy systems into cloud-native data architectureBuild pipelines that power AI, analytics, fraud detection, and customer insightsContribute to systems that enable real-time business decisions at scaleWhat You'll Work On (Real Banking Data Modernization Projects)Cloud Data ModernizationSupport migration from legacy systems to Azure + Databricks LakehouseWork with structured, semi-structured, and streaming dataHelp build scalable, cloud-native data platformsData Engineering & PipelinesBuild and optimize ETL/ELT pipelines using:Python / PySparkSQLDatabricks WorkflowsWork with Delta Lake architectureData Analytics & AI EnablementEnable data for:Customer insightsFraud detectionRisk analyticsOperational reportingSupport ML/AI use cases using curated datasetsData Governance & QualityEnsure data accuracy, consistency, and lineageWork with governance frameworks (e.g., Unity Catalog concepts)Support regulatory-grade data reportingData Products & Business InsightsBuild datasets powering dashboards (Power BI/Tableau)Support creation of data products used by business teamsHelp transform raw data into actionable insightsWhat We're Looking For (Fresh Graduate Profile)Education: Bachelor's or Master's in:Computer ScienceData Science / AnalyticsInformation SystemsEngineering (any discipline with data exposure)Core Skills (Must Have Potential):Strong fundamentals in:SQLPython (or willingness to learn)Understanding of:Data structuresBasic ETL conceptsAnalytical thinking and problem-solving mindsetBonus (Nice to Have):Exposure to:PySpark / SparkCloud platforms (Azure preferred)Data visualization (Power BI / Tableau)Knowledge of:Data warehousing conceptsAPIs and data integrationWhat You Will Learn (Career Acceleration Path)This program is designed to fast-track you into:Data Engineer → Senior Data Engineer → Data Architect → AI/Data LeaderYou will gain hands-on experience in:Azure Data Ecosystem (ADF, Databricks, Storage)Lakehouse Architecture (Delta Lake)Data Engineering at enterprise scaleAI/ML data pipelinesFinancial services data systemsWhy 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.