Data Analyst/Developer (Assistant Vice President)

Job description

Position Summary:

We are seeking a highly experienced and strategic Senior Data Analyst/Developer with over 12+ years of progressive experience, possessing a robust background in data analysis, business intelligence, and a deep understanding of data warehousing concepts, including PL/SQL, ETL processes, IBM DataStage, and Enterprise Application Integration (EAP).

The ideal candidate will be a critical thinker with exceptional analytical skills, capable of translating complex data into actionable insights for business stakeholders.

The successful candidate will be instrumental in Data Analysis for Genesis Application which delivers Regulatory & Consent Order items for Regulatory & Fed Reports.

This role requires not only strong technical acumen but also significant experience in leading data initiatives, mentoring junior analysts, and influencing data strategy.

Key Responsibilities

• Advanced Data Analysis & Insight Generation: Lead complex data analysis initiatives to identify trends, patterns, and anomalies in large datasets.
  
  Develop sophisticated reports, dashboards, and analytical models to provide actionable insights that drive business decisions across various departments.
  
  
• Requirements Gathering & Solution Design: Collaborate extensively with business stakeholders (e.g., product managers, marketing, finance, operations) to deeply understand their analytical needs and business questions.
  
  Translate these into detailed data requirements and propose optimal analytical solutions.
  
  
• Data Sourcing & Transformation: Work closely with Data Engineers and ETL developers to identify, source, and ensure the availability and quality of necessary data.
  
  Utilize strong understanding of PL/SQL to query complex relational databases and validate data accuracy.
  
  
• ETL Process Understanding & Validation: Leverage deep knowledge of ETL processes, particularly with IBM DataStage, to understand data lineage, transformations, and potential impacts on data analysis.
  
  Proactively identify data quality issues within ETL pipelines and work with engineering teams for resolution.
  
  
• Enterprise Application Integration (EAP) Context: Understand how data flows through various enterprise applications via EAP layers.
  
  This knowledge will be crucial for comprehending data availability, latency, and consistency for accurate analysis.
  
  
• Data Modeling & Architecture Awareness: Possess a solid understanding of data warehousing concepts, dimensional modeling, and database schemas.
  
  Provide input and feedback on data model designs from an analytical consumption perspective.
  
  
• Reporting & Dashboarding: Design, develop, and maintain advanced business intelligence solutions, including interactive dashboards and automated reports, using industry-leading BI tools.
  
  
• Mentorship & Guidance: Provide technical guidance, mentorship, and support to junior data analysts.
  
  Share best practices in data extraction, analysis, visualization, and communication.
  
  
• Data Governance & Quality: Champion data quality and integrity.
  
  Develop and implement data validation rules and processes to ensure the reliability and accuracy of analytical outputs.
  
  Adhere to organizational data governance policies.
  
  
• Performance Optimization (Analytical): Optimize complex SQL queries and data extraction processes to ensure efficient data retrieval for analysis and reporting.
  
  
• Communication & Presentation: Clearly and effectively communicate complex analytical findings, insights, and recommendations to both technical and non-technical audiences through compelling presentations and written reports.
  
  
• Strategic Contribution: Contribute to the overall data strategy, helping to define key metrics, identify data gaps, and recommend data infrastructure improvements.
  
  

Required Qualifications

• Experience: Minimum of 15 years of progressive experience in a Data Analyst, Business Intelligence Analyst, or similar role, with a strong focus on enterprise-level data.
  
  
• PL/SQL Expertise: Advanced proficiency in writing complex SQL queries and PL/SQL scripts for data extraction, manipulation, and analysis from large relational databases (preferably Oracle).
  
  
• ETL & Data Warehousing Knowledge: In-depth understanding of ETL processes, data warehousing principles, dimensional modeling (star schema, snowflake schema), and concepts like Slowly Changing Dimensions (SCDs).
  
  
• DataStage Familiarity: Solid understanding of IBM DataStage or similar enterprise-grade ETL tools, including the ability to understand job flows, source-to-target mappings, and data transformations.
  
  While not a developer role, the ability to comprehend complex DataStage implementations is crucial.
  
  
• EAP Awareness: A good understanding of Enterprise Application Integration (EAP) concepts and how data moves across different business systems via integration layers (e.g., APIs, message queues).
  
  
• BI Tool Proficiency: Expert-level experience with at least one leading Business Intelligence/Visualization tool (e.g., Tableau, Power BI, Qlik Sense, Cognos).
  
  
• Analytical Skills: Exceptional analytical, quantitative, and problem-solving skills with a proven ability to interpret data, analyze results, and provide data-driven recommendations.
  
  
• Communication: Excellent verbal and written communication skills, with a proven ability to present complex analytical findings clearly and concisely to diverse audiences.
  
  
• Data Governance & Quality: Strong commitment to data quality, accuracy, and governance.
  
  
• Mentorship: Demonstrated experience in mentoring and guiding less experienced team members.
  
  

Preferred Qualifications

• Bachelor's or Master's degree in a quantitative field such as Computer Science, Statistics, Mathematics, Economics, or Business Administration.
  
  
• Experience with statistical analysis tools (e.g., R, Python with Pandas for advanced analytics.
  
  
• Familiarity with cloud-based data platforms (e.g., AWS Redshift, Azure Synapse, Google BigQuery).
  
  
• Experience with big data technologies (e.g., Hadoop, Spark).
  
  
• Domain expertise in a specific industry (e.g., Finance, Banking).
  
  

#LI-Hybrid

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Job Family Group:

Technology

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Job Family:

Applications Development

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Time Type:

Full time

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Most Relevant Skills

Please see the requirements listed above.

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Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.

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Required Skill Profession

Risk Management & Quantitative Analysis