Senior Data Analyst - Digital Analytics & Business Intelligence (Hybrid)

First Citizens Bank-posted 3 months ago
Hybrid • Raleigh, NC
5,001-10,000 employees
Credit Intermediation and Related Activities
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This is a hybrid role that may only be hired in North Carolina, with the expectation that time working will regularly take place inside and outside of a company office. First Citizens Bank (FCB) has a 125-year history of financial strength, stability, and innovation. As part of our digital transformation journey, we are investing in data and technology to power smarter decisions, enable better customer experiences, and drive growth across all digital channels. The Digital Analytics team plays a critical role in this mission by turning raw data into actionable insights. We partner closely with Product, Go-to-Market, Customer Support, UX, Technology, and Enterprise Data and Governance teams to build the digital analytics foundation that empowers better decision-making and a seamless customer journey. We are seeking a Senior Data Analyst to join our Digital Analytics and Business Intelligence team. This role is ideal for someone passionate about data and insights, with strong technical skills and the ability to partner with cross-functional teams to solve complex problems and a strong drive for workflow automation. You will build foundational data models and reports to provide near real time insights, champion best practices, and mentor junior analysts, all while directly impacting our ability to deliver value to customers and business stakeholders.

  • Identify, source, and validate data across multiple systems; ask the right questions to uncover data-producing processes.
  • Balance rapid market delivery with a sustainable, scalable design.
  • Transform raw data into meaningful insights through advanced analytics, visualization (Tableau), and walkthroughs with stakeholders.
  • Build custom algorithms and processes that support initiatives such as digital platform integrations and expansions.
  • Partner with Tech and Enterprise Data Warehouse (EDW) teams to procure and ingest vendor data into centralized repositories.
  • Design and build digital domain specific data models.
  • Design, manage, and schedule lean ETL pipelines for robust, scalable data flows.
  • Oversee service IDs, deployment processes, and administrative tasks tied to data operations.
  • Create and maintain data flow and data mapping documents.
  • Collaborate with Data Stewards and Governance teams to ensure data integrity, compliance, and alignment with enterprise standards.
  • Champion best practices in data architecture, modeling, and governance.
  • Serve as a key analytics partner to Product, UX, Go-to-Market, and Customer Support teams.
  • Translate business needs into data solutions, delivering actionable insights that drive decisions.
  • Manage offshore contractors and vendor resources, ensuring high-quality deliverables and consistent status reporting.
  • Mentor junior analysts, fostering skill development and knowledge sharing.
  • Drive a 'get stuff done' culture, with strong problem-solving, execution, and communication skills.
  • Bachelor's degree in Data Science, Statistics, Computer Science, or related field.
  • Strong expertise in SQL, ETL development (Python, Informatica, SAS or Airflow, and Tableau, PowerBI or equivalent BI tools).
  • Hands-on experience with data modeling, data architecture, and building custom algorithms.
  • Proven ability to manage offshore resources and contractors.
  • Excellent communication, presentation, and stakeholder engagement skills.
  • Comfortable with ambiguity and stakeholder management across multiple business functions.
  • Familiarity with project management concepts, such as agile practices.
  • 7+ years' experience in data analytics, business intelligence, or related role. Master's degree is a plus.
  • Digital experience software like Google Analytics, Quantum metrics etc.
  • Statistical software, or coding languages (e.g., Python, R, SAS).
  • Statistical or quantitative analysis (e.g., multiple regression, multivariate analysis, network analysis, AI-ML concepts and techniques).
  • Experience with Natural Language Processing (NLP) algorithms, tools, customer/employee survey analyses, segment analysis and pattern detection, etc.
  • Familiarity with cloud computing approaches, such as IBM Netezza, AWS, Azure, etc.
  • Familiarity or hands-on experience with data science, machine learning, and AI.
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