What are the responsibilities and job description for the Sr. Data Analyst position at Discovery, Inc.?
Overview
he Senior Data Analyst will be an integral part of Discovery’s growing Data Strategy & Analytics team in support of DTC initiatives, specifically focusing on customer journey and 1st Party Data. The person will be a data product owner, technical business resource, and data analyst. Collaborating with stakeholders from across Discovery to identify and address their data needs, building analytical solutions to meet those needs, and driving actionable insights.
This person will be a key technical leader of projects from the planning stages to requirements gathering through final product delivery. They must possess the ability to speak to results, and clearly explain complex data to non-technical stakeholders. Thus, it requires a person with strong analytics experience, who is interested in product and project management, and comfortable working across multiple business units.
As a hands-on technical role, the ability to assess gaps in functionality and pitch creative technical solutions in a way that suits our business needs is essential. Synthesizing large disparate data sets from multiple sources, writing SQL queries, and navigating scripts to execute them will be daily tasks.
The Senior Analyst will be at home with the use of data analysis to better understand customer journeys and user behavior, enhance our products, and more. Organizational skills, a creative approach to problem solving, and a desire to understand the business context driving decisions is vital. Self-starters and self-taught programmers with relevant professional experience are encouraged to apply.
Responsibilities
Key Areas of Responsibility
Data Solutions and Project Management
- Work with managers and business stakeholders to fully understand business requirements and desired outcomes of their analytics needs.
- Implement data structures and visualisations that enable senior management to analyse and action high value business decisions. This requires understanding the business objectives along with the complexity of the underlying datasets, developing a plan to implement, and seeing that through to execution.
- Develop relationships with teams across Discovery to understand and advance their data needs in a holistic manner across multiple projects.
- Introduce standardised project management tools to be used across the data organization
Data Structure, Engineering, and Workflow:
.
- Troubleshoot data access issues.
- Work closely with the Data Engineering team to extract, transform and load new data sources into Discovery’s central data lake.
- Test pipelines and validate data coming from various sources to make sure it is accurate, legible, clean and transformed before reporting is performed.
- Design and build data tables.
- Create and update comprehensive documentation on workflows, pipelines, and other data processes.
Data Analytics
- Write SQL queries and Python scripts to perform analysis.
- Scope and design analytical projects and solutions with a focus on global analytics, ensuring the project, technical structure, and data elements are scalable.
- QA and test various calculations of dashboards based on business requirements
- Generate queries & data dictionaries, analyse data and create visualization/dashboards related to audience and direct-to-consumer insight
- Support roll-out of multiple sprints as a key technical resource
- Identify opportunities to create and automate repeatable analysis or build self-service tools for business users.
Qualifications
Bachelor’s degree in Computer Science, Data Analytics or related field and 2- 5 years experience as a data analyst, business analyst, data engineer, data scientist or related position. Or multiple years working experience with ad tech, cloud, or data platforms.
- Ability to work in a fast-paced environment with at least 5 years of work experience.
- Proficiency in SQL and hands-on experience with relational databases is a must.
- Deep experience in developing queries and reporting based upon user requirements.
- Experience with data visualisation tools such as Tableau and Power BI.
- An understanding of Cloud services.
- 1 year of experience with the following is preferred:
o Amazon Web Services or similar cloud computing platform;
o Project management;
o Linux based command lines;
o Script execution;
o Tableau;
o SQL
o Python (or similar scripting languages: Ruby, JS, etc..),
o Marketing goals, campaigns, and strategy.
Responsibilities:
Key Areas of Responsibility Data Solutions and Project Management - Work with managers and business stakeholders to fully understand business requirements and desired outcomes of their analytics needs. - Implement data structures and visualisations that enable senior management to analyse and action high value business decisions. This requires understanding the business objectives along with the complexity of the underlying datasets, developing a plan to implement, and seeing that through to execution. - Develop relationships with teams across Discovery to understand and advance their data needs in a holistic manner across multiple projects. - Introduce standardised project management tools to be used across the data organization Data Structure, Engineering, and Workflow: . - Troubleshoot data access issues. - Work closely with the Data Engineering team to extract, transform and load new data sources into Discovery’s central data lake. - Test pipelines and validate data coming from various sources to make sure it is accurate, legible, clean and transformed before reporting is performed. - Design and build data tables. - Create and update comprehensive documentation on workflows, pipelines, and other data processes. Data Analytics - Write SQL queries and Python scripts to perform analysis. - Scope and design analytical projects and solutions with a focus on global analytics, ensuring the project, technical structure, and data elements are scalable. - QA and test various calculations of dashboards based on business requirements - Generate queries & data dictionaries, analyse data and create visualization/dashboards related to audience and direct-to-consumer insight - Support roll-out of multiple sprints as a key technical resource - Identify opportunities to create and automate repeatable analysis or build self-service tools for business users.