Technical Data Analyst
1 month ago
Job Summary: We are seeking a highly skilled and motivated Technical Data Analyst with a strong background in quantitative data analysis and technical expertise in data warehousing, SQL, and analytical tools. The ideal candidate will have a proven ability to manage and analyze large datasets, leverage AWS services, and communicate complex data insights effectively to both technical and non-technical stakeholders.
Key Responsibilities:
- Perform end-to-end quantitative and qualitative analysis on large datasets to derive meaningful insights and support business decision-making.
- Develop complex SQL queries from scratch to extract, segment, and aggregate data from data warehouses.
- Utilize data query and processing tools/systems, including relational, NoSQL, and stream processing databases.
- Collaborate closely with cross-functional teams to understand data needs and design effective data models.
- Use AWS services such as Redshift and Athena, and demonstrate an understanding of AWS core concepts to optimize data operations.
- Implement and manage data modeling techniques using tools such as Python, R, and PyCharm.
- Present complex technical information in a clear and concise manner to executives and non-technical stakeholders.
- Work independently as a self-starter, applying critical thinking and creativity to solve problems.
- Stay curious and continuously improve processes by learning new techniques and technologies.
- Quickly adapt and get up to speed on business systems such as Salesforce, Amazon Connect, and EWFM, and understand their data architecture and interactions.
Qualifications:
- Experience: 5+ years in quantitative data analysis, data engineering, or a related field.
- Education: Technical undergraduate degree in Engineering, Computer Science, Statistics, Analytics, or equivalent experience.
Technical Skills:
- Advanced SQL proficiency
- Experience with AWS (Redshift, Athena) and core AWS concepts
- Knowledge of data query and data processing systems (relational, NoSQL, stream processing)
- Familiarity with data modeling techniques
- Experience with analytical tools like Python, R, or PyCharm
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