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Requirements
Top 3 Requirements:

• Experience in leadership managing a team of data analysts, scientists, or engineers
• 7+ years of experience with Data manipulation and statistical modeling as a Scientist, Consultant, Architect, DBA, or Engineer
• Using a data science toolkit such as Python or R
• There will be a big focus on ETL creation and flattening tables for analytics use in cloud environments

• Preferred Qualifications
• Experience: One or more scripting, analysis, or ETL languages and ability to rapidly learn new languages or techniques; Large data sets and the tools to obtain, transform, and store data on Big Data and streaming services

Day to Day/Project:

The Data Insights Manager will be responsible for managing a team that creates and maintains databases for test, development and production environments. Analyzes, tests, and implements physical database designs. They will manage complex and diverse projects simultaneously; manage development within a variety of technology stacks; adapt, learn, and continue to expand cable and IP product system knowledge; demonstrated understanding of problem resolution techniques and ability to find solutions; communicate effectively with internal and external customers both verbally and in writing; possess the ability to build trusted business partnerships, incorporate partner experience and feedback into overall product development and identify expansion opportunities, supervise and motivate others. The Manager creates and maintains databases for test, development and production environments. Analyzes, tests, and implements physical database design. Documents environment and maintains current patches. Ensures data recovery, maintenance, data integrity, and space requirements for physical database are met through formulation and monitoring of policies, procedures, and standards relating to database management. Audits the current environments, provides capacity planning and best practices for the future production/development/test environments, which may include establishing new standards and procedures. Conducts performance assessment and tuning as related to the database system. Provides technical knowledge working with system administrators, technical managers, developers, and architects.

Day to Day Breakdown %:

• Managing a team that does the following:
• Data Pipeline Development and Maintenance (30-40%)
• Building and maintaining ETL process from various sources into company data environment like snowflake, azure, fabric. Also involves building views and monitoring pipelines to ensure they run smoothly.
• Data Modeling and Prototyping (20-25%)
• Designing and prototyping new data structures and exploring how to leverage new tools or platforms (like azure and fabric). This includes creating proof-of-concept models and ensuring data is organized for easy access and analysis.
• * Collaboration and Requirements (15-20%)
• Working with other teams to understand data needs, defining requirements, and creating data views that can be shared across the organization.
• Data Integration and Governance (10-15%)
• Ensuring proper data governance, security, and access control. This also includes integrating data from various sources to create a unified and comprehensive dataset.
• Testing and Quality Assurance (10%)
• Regularly testing data pipelines, validating data accuracy, and ensuring the integrity of the data structures.

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