Data Analyst

About the Role: Data Analyst, 1. Data Analysis & Insights: Collect, clean, and analyze large datasets to identify trends, patterns, and operational performance metrics.

2. Dashboard & Reporting: Design, build, and maintain interactive dashboards and automated reports using tools like Power BI, Tableau, or Looker.
3. Cross-Functional Collaboration: Partner with product, business, and engineering teams to define key performance indicators (KPIs) and deliver actionable recommendations.
4. Data Modeling & Querying: Write efficient SQL queries to extract data from databases and data warehouses, maintaining data accuracy and integrity.
5. Process Automation: Streamline data collection and reporting workflows using scripting languages like Python or R.
6. Documentation & Quality: Document data definitions, analytical processes, and reporting methodologies to ensure consistency and quality control., 1. Targeted Placement: Direct marketing to our network of hiring managers in the Data, Technology, and Business Analytics sectors.
7. Technical Resume Rebuild: Optimization of your profile to highlight data analytics tools, SQL proficiency, and business impact.
8. Interview Coaching: Guidance on behavioral questions, SQL technical assessments, and data case studies.

We are seeking a detail-oriented Data Analyst to turn raw data into actionable insights, build interactive dashboards, and support data-driven decision-making across cross-functional teams. In this role, you will analyze complex datasets, maintain data pipelines, and partner with stakeholders to solve business problems and optimize performance., 1. Education: Bachelor's degree in Data Analytics, Computer Science, Statistics, Information Systems, Business Administration, or a related field (Required).

2. Experience: 0-5 years of experience in data analytics, business intelligence, or reporting.
3. Technical Skills (Required):

• Strong proficiency in SQL for data querying and extraction.
• Hands-on experience with data visualization platforms (Power BI, Tableau, Looker).
• Solid understanding of relational databases and data warehouse concepts.
• Scripting ability in Python or R for data analysis and manipulation (Pandas, NumPy).
• Advanced knowledge of Microsoft Excel (PivotTables, Advanced Formulas, Power Query).

1. Preferred Skills:

• Relevant certifications (e.g., Microsoft Certified: Data Analyst Associate, Tableau Desktop Specialist).
• Familiarity with cloud analytics environments (AWS Redshift, Google BigQuery, Snowflake).
• Knowledge of statistical methods and basic predictive modeling techniques.