Job description
Position: SQL / Python Data Analyst
Location: Redmond WA (Hybrid)
Duration: 6+ months contract (possible extension)
W2, & without sponsorship now and in future.
Primary Responsibilities
Location: Redmond WA (Hybrid)
Duration: 6+ months contract (possible extension)
W2, & without sponsorship now and in future.
Primary Responsibilities
- Develop, maintain, and enhance staffing and workforce planning models.
- Build and optimize data pipelines using Azure Data Factory (ADF) and related Azure services.
- Develop analytical solutions and automation using SQL and Python.
- Manage and support Azure SQL environments, including database administration, monitoring, and performance tuning.
- Support data integrations, ETL processes, and reporting solutions.
- Work with tabular data models, including SSAS cubes.
- Ensure data quality, reliability, and scalability across planning and reporting platforms.
- Partner with business stakeholders to translate workforce planning requirements into analytical solutions.
- Advanced SQL development and database design expertise.
- Strong Python programming skills for data analysis, automation, and data engineering tasks.
- Experience with Azure SQL Database administration, performance tuning, and troubleshooting.
- Azure Data Factory (ADF) pipeline development and maintenance experience.
- Experience building and maintaining analytical and forecasting models.
- Familiarity with SQL Server Analysis Services (SSAS) cubes and dimensional modeling.
- Understanding of Azure data platform services and cloud-based data architectures.
- Strong analytical, troubleshooting, and communication skills.
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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.
