Midlevel Data Analyst

As a Data Analyst, you are expected to be a technical reference regarding data analysis and DataOps practices within the specialty—resolving questions, sharing knowledge, driving process improvements, and staying aligned with industry trends.

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Responsabilities

As a Data Analyst, your responsibilities will include:

Creating, making available, evolving, and maintaining data products based on our clients’ business needs; designing, creating, and improving dashboards and custom scripts for advanced data analysis and business KPI monitoring.

Contributing to discussions on data storage and data pipelines to support advanced analytical reporting, as well as data analysis and exploration, using various data and visualization technologies.

Working closely with analytics engineers and data product managers to identify process improvements and align these changes with team practices.

Collaborating with stakeholders by providing guidance, data, and analytical support for the development of new analyses and tools that support strategic initiatives.

Suggesting/Collaborating/Developing and facilitating initiatives with the data governance team to ensure data integrity across distributed systems.

Encouraging and promoting DataOps practices in the development of data products.

Suggesting/Collaborating/Driving experiments, innovations, and the resolution of complex problems.

Suggesting/Collaborating/Promoting an analytical and data-driven decision-making culture at Blip through training sessions, workshops, and knowledge transfer related to data analysis products.

Suggesting/Collaborating/Promoting and disseminating good data governance and data quality practices.

Sharing knowledge and supporting the outputs produced by the team.

Requirements

What we expect from you:

Advanced expertise in database concepts/data modeling, strong SQL skills, and proficiency in query performance optimization.

Proficiency in exploratory data analysis.

Proficiency in developing Power BI Desktop and Service solutions, focusing on optimization and organization of resources for large-scale use.

Knowledge of Python and Spark for large-scale data processing.

Knowledge of GIT technology.

Proficiency in data visualization and storytelling.

Experience in statistical modeling.

Experience with data testing practices.

Ability to work effectively in a team environment and build partnerships with both technical and business team members.

Ability to translate technical language for non-technical audiences.

Strong collaboration, curiosity, communication, leadership, and organizational skills.

It will be a plus if you have:

Experience using DataBricks.

Knowledge of Machine Learning.

Previous experience in the conversational industry. xcskxlj

Client-facing experience.

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