Senior Data Analyst

  • Mountain View, CA
  • Posted 17 days ago | Updated 17 days ago

Overview

On Site
Hybrid
Depends on Experience
Contract - W2
Contract - Independent

Skills

Databricks
Snowflake
Python
AI/ML platforms
SQL

Job Details

Duration: 6 Months

Location: Bay Area, CA Mondays and Tuesdays onsite

Our client is seeking a highly skilled and experienced Senior Data Analyst to join their growing team as they leverage data-driven insights to optimize their operations.

Technical Qualifications:

  • Proven experience as a Data Analyst or similar role, preferably in the oil and gas industry.
  • Strong knowledge of data analysis tools and programming languages (e.g., Python, SQL, R) to extract, clean, manipulate, and analyze large datasets.
  • Proficiency in data visualization tools such as Power BI/Tableau to create meaningful and insightful reports and dashboards.
  • Experience with database systems (e.g., Databricks, Snowflake, BQ, Oracle, Microsoft SQL Server) and cloud data warehousing concepts.
  • Excellent problem-solving skills with a keen eye for detail and ability to see the bigger picture.
  • Experience with Automation and Understanding of AI/ML platforms and data requirements to facilitate development of AI/ML models
  • Strong communication and interpersonal skills, with the ability to effectively collaborate with and present findings to technical and non-technical stakeholders.
  • Demonstrated leadership skills, with the ability to mentor and guide a team of analysts.
  • Strong organizational skills and ability to manage multiple projects simultaneously.
  • Stay up-to-date with the latest advancements and best practices in data analysis, data management, and data visualization techniques.

Key Responsibilities:

  • Play a crucial, lead role in departmental/company data analytics efforts.
  • Collaborate closely with cross-functional teams, including Finance, Sales Operations, and Engineering, to identify business needs and establish data analysis requirements.
  • Design and implement data collection, integration, and retention strategies to ensure reliable and high-quality datasets.
  • Develop, maintain, and enhance data models, algorithms, and statistical models to extract insights and forecast key business metrics.
  • Analyze complex datasets using advanced statistical techniques and data visualization tools to identify trends, patterns, and correlations.
  • Present analytical findings and recommendations to key stakeholders, including senior management, in a clear and concise manner.
  • Drive the deployment of analytical solutions and tools, providing support and training to end-users for effective utilization.