About Rootshell
Sourced by ZipRecruiter
Industry
It services
Company size
51 - 200 Employees
Headquarters location
Santa Clara, CA, US
Year founded
2000
Other
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Job description
Data Analyst/Engineer
Greetings from Rootshell Enterprise Technologies Inc.
Rootshell Enterprise Technologies Inc. is a recognized provider of professional IT Consulting services in the US. We are actively seeking a Data Analyst/Engineer for one of our clients.
Job Summary:
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
Experience with SQL, ETL, data modeling, and at least one programming language (e.g., Python, C++, C#, Scala, etc.)
4+ years of experience querying non-relational databases using SQL or Python.
4+ years of experience working in an analytical capacity developing insights, defining metrics, and making recommendations.
Presentation and communications experience with extracting insights from technical data sets to varied audiences.
Experience thinking strategically about complex issues, leading to thoughtful recommendations and action plans.
Responsibilities:
Collaborate with engineers, product managers and data scientists to understand data needs, representing key data insights in a meaningful way.
Build data expertise and leverage data controls to ensure privacy, security, compliance, data quality, and operations for allocated areas of ownership.
Design, build and launch new data models and visualizations in production, leveraging common development toolkits.
Support existing processes running in production and implement optimized solutions with limited guidance.
Build dashboards and reports to track effectiveness and efficiency improvements over time, and guide future decisions.
Establish close working relationships with a variety of cross-functional stakeholders including deal leads, data engineering, and product development teams.
With regards, Naveen | Talent Acquisition Rootshell Enterprise Technologies Inc.
rootshellinc.com
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Frequently asked questions
Q: What skills or qualities help someone succeed as a Data Analyst?
A: To succeed as a Data Analyst, key technical skills include proficiency in programming languages such as Python or R, expertise in data visualization tools like Tableau or Power BI, and knowledge of statistical analysis and machine learning concepts. Additionally, strong soft skills like effective communication, problem-solving, and collaboration are crucial for presenting insights to stakeholders and working with cross-functional teams. By combining these technical and soft skills, Data Analysts can drive business decisions, identify areas for improvement, and contribute to the growth and success of their organization.
Q: What is the career path for a Data Analyst?
A: A Data Analyst's typical career progression involves starting as an Entry-Level Data Analyst, where they collect, analyze, and interpret data to inform business decisions. As they gain experience, they can move into Mid-Level roles such as Senior Data Analyst or Business Analyst, where they take on more complex projects and lead smaller teams. Ultimately, they can advance to Senior Leadership positions like Data Scientist, Data Manager, or even Director of Analytics, where they oversee large-scale data initiatives and drive strategic business growth.\n\nKey opportunities for skill development and professional growth in this role include learning programming languages like Python or R, mastering data visualization tools like Tableau or Power BI, and staying up-to-date with emerging trends in machine learning and artificial intelligence. Additionally, Data Analysts can develop soft skills like communication, project management, and leadership to excel in their roles.\n\nLong-term career prospects for Data Analysts are diverse, with potential directions including transitioning into related fields like Business Intelligence, Data Engineering, or even becoming a Product Manager, or pursuing advanced degrees in Data Science or related fields to further specialize in areas like machine learning or data engineering.