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Data Analyst
Audubon, PAThe primary function of the Senior Data Analyst is to leverage the flexibility and scalability of the data lake environment to drive advanced analytics, support strategic decision-making, and promote data democratization across the organization. This will be achieved by providing deep expertise in developing, managing, and owning high-quality business, technical, and functional requirements. A key focus will be on conducting analysis using real-time time-series data to support the enterprise and the ongoing expansion of the platform.
Responsibilities
Responsibilities
- Identify, prepare, and curate data for analysis and visualization, ensuring alignment with business objectives.
- Cleanse, map, transform, and optimize data for storage and analytical use, adhering to both technical and business requirements.
- Proactively identify opportunities for process improvement and implement automation to enhance efficiency.
- Load and manage transformed data within data warehouses, real-time reporting systems, and analytics platforms.
- Analyze complex datasets to draw actionable insights and provide data-driven recommendations.
- Fully document, own and manage business, technical and functional requirements throughout the full project lifecycle.
- Design, test, and validate changes to data domains, reports, and data quality routines using SQL.
- Develop proof-of-concept prototypes to demonstrate and evaluate analytical solutions.
- Collaborate closely with Data Architects to ensure adherence to best practices in data design and architecture.
- Minimum of 8 years of experience in data analysis, data science, or a related field.
- Bachelor’s degree in computer science, Information Systems, Engineering, or equivalent experience.
- Proven experience working with large, complex datasets and big data environments.
- Strong proficiency in Oracle PL/SQL (preferred).
- Familiarity with tools such as Microsoft Purview, Snowflake, Qlik, and Tableau.
- Experience with Databricks and data warehouse architectures, including relational table structures.
- Expertise in performance- and security-oriented data modeling, including partitions, indexing strategies, and data management best practices.
- Experience contributing to data architecture, including the development of data models and ETL processes.
- Ability to develop and maintain source-to-target mapping documentation for ETL workflows.
- Skilled in cross-platform data analysis using Entity Relationship Diagrams (ERDs).
- Hands-on experience designing ETL processes, conducting data profiling, and implementing data quality routines for internal and external stakeholders.
- Open-minded and adaptable, with a strong ability to learn new technologies and methodologies quickly.
- Strong skills in requirements elicitation, documentation, and stakeholder communication.
- Excellent collaboration, presentation, and interpersonal skills.
- Self-starter with the ability to manage and deliver projects with minimal supervision.
- Comfortable working in fast-paced environments and pivoting in response to changing requirements.
- Experience in testing and validating data domain changes, including analytics, reporting, and data quality routines using SQL.
- Demonstrated ability to monitor and analyze KPIs and financial metrics to support strategic decision-making.