Data Engineer

Data Analyst/Engineer
Position Summary:
We are seeking a highly motivated and skilled Data Analyst to join the dynamic team. As a Data Analyst, you will play a pivotal role in collecting, analyzing, and interpreting data to inform our advertising and marketing strategies within the industry. The ideal candidate will have a passion for data-driven decision-making and a strong ability to extract actionable insights.
Experience and Education:

• B.S. in Computer Science, Data Science, or related experience
• 4+ years work experience as Data analyst or related field experience
• Proficiency in SQL data analysis tool
• Knowledge of data visualization tools
• Strong analytical and problem solving skills

Skills and Strengths:

• SQL
• PostgreSQL
• SQL queries
• ETL
• ETL processes
• Data modeling
• Data pipelines
• Data warehouse
• Data manipulation
• Data visualization tools (i.e., Tableau, Power BI, QlikView)
• Hangfire
• Git
• Python (a plus)
• .Net (a plus)
• C# (a plus)

Primary Job Responsibilities:

• Gather data from various sources, including databases, spreadsheets, APIs, and external datasets. Ensure the data collected is accurate, complete, and relevant.
• Clean and preprocess data to make it suitable for analysis. This involves tasks such as handling missing data, removing duplicates, and standardizing data formats.
• Apply statistical and analytical techniques to data sets to identify trends, patterns, correlations, and meaningful insights.
• Prepare reports and presentations summarizing analysis results. These reports often include key insights, recommendations, and actionable takeaways for decision-makers.
• Conduct hypothesis tests to validate findings and assess the statistical significance of observed trends.
• Interpret the results of data analysis in the context of the organization's goals and objectives.
• Implement data quality checks, validation processes, and monitoring to ensure data integrity and accuracy.
• Stay updated with industry trends, emerging tools, and best practices in data analysis. Continuously improve skills and knowledge in data analytics.
• Explore data to discover hidden patterns, anomalies, or outliers that might provide valuable insights beyond the initial analysis.
• Maintain documentation for data analysis processes, methodologies, and assumptions to ensure transparency and knowledge sharing within the organization.