Technical Leadership:
- Provide technical guidance and mentorship to a team of data analysts.
- Set technical standards and best practices for data analysis projects.
- Stay abreast of the latest technologies and trends in data analytics.
- Make recommendations for technology adoption and implementation.
- Oversee the design and development of data pipelines, ETL processes, and data models.
- Ensure data quality and integrity throughout the data lifecycle.
Project Management:
- Collaborate with stakeholders and PMs to gather requirements and define project scope.
- Develop project plans and timelines.
- Manage project resources and budgets.
- Track project progress and report to stakeholders.
- Mitigate risks and address project challenges.
Data Analysis and Visualization:
- Perform complex data analysis using advanced statistical and analytical techniques.
- Develop and implement data visualization solutions to communicate insights effectively.
- Provide actionable insights and recommendations based on data analysis.
Collaboration and Communication:
- Work closely with cross-functional teams, including data engineers, data scientists, and business stakeholders.
- Communicate technical concepts to non-technical audiences.
- Foster a culture of collaboration and knowledge sharing within the team.
Innovation and Continuous Improvement:
- Identify opportunities for innovation and process improvement.
- Implement new tools and techniques to enhance data analysis capabilities.
- Promote a culture of continuous learning and development within the team.
Specific Skills:
- Proficiency in SQL. Familiar with Python, Go. Working on Julia Knowledge.
- Experience with Power BI and Looker as data visualization tools.
- Familiarity with Azure and GCP.
- Familiarity with DevOps and Jira for tracking.
- Strong analytical and problem-solving skills.
- Excellent communication and interpersonal skills.More...