JOB DESCRIPTION OF THE DATA ENGINEER AT PULSE NG

• We are seeking a data-driven and technically proficient Data Engineer with a strong analytical background to join our online media company.
• In this role, you will bridge the gap between data engineering and data analysis, building and maintaining our data infrastructure while wielding your analytical skills to extract valuable insights.You will collaborate closely with cross-functional teams to ensure our data pipelines are optimized to deliver actionable information that drives strategic decision-making for our digital media platforms and enhances the user experience.

QUALIFICATIONS OF THE DATA ENGINEER AT PULSE NG

• A degree in Data Science, Statistics, Computer Science, or a related field is preferred but not mandatory.
• Professional experience: 5 years of experience as a Data Analyst or a similar role, preferably within the online media industry. Experience in analyzing web analytics data and digital media platforms is highly desirable.
• Data analysis and visualization: Proficiency in data analysis techniques, statistical methods, and data visualization tools (e.g., Excel, Tableau, Power BI, Google Data Studio). Ability to distill complex data into meaningful insights.
• SQL and data querying: Strong SQL skills and experience in querying and manipulating data from relational databases. Familiarity with data modeling concepts.
• Web analytics tools: Experience with web analytics tools such as Google Analytics, Adobe Analytics, or Mixpanel. Knowledge of event tracking, conversion tracking, and user behavior analysis.
• A/B testing and experimentation: Familiarity with A/B testing methodologies and experimentation frameworks. Experience with A/B testing tools, such as Optimizely or Google Optimize.
• Data-driven mindset: Strong problem-solving and critical thinking skills with a focus on data-driven decision-making. Ability to identify relevant metrics, analyze complex data sets, and provide actionable insights.
• Strong communication skills: Excellent written and verbal communication skills to present complex data and insights clearly and understandably to both technical and non-technical stakeholders.Attention to detail: Strong attention to detail and accuracy in data analysis and reporting. Ability to spot data anomalies and investigate discrepancies.
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• Collect, clean, and analyze data from various sources, including web analytics tools, databases, and external APIs.
• Use statistical techniques and data mining methods to uncover patterns, trends, and insights.
• Design, develop, and maintain scalable data pipelines to ingest, transform, and store data from various sources.
• Develop and maintain reports, dashboards, and visualizations to effectively communicate data-driven insights to stakeholders.
• Utilize tools such as Tableau, Power BI, or Google Data Studio to present data in a visually appealing and understandable manner.
• Define key performance indicators (KPIs) and track the performance of digital media platforms.
• Analyze KPIs to identify areas for improvement and provide recommendations for optimization.
• Analyze user behavior data to understand user preferences, engagement patterns, and conversion funnels.
• Provide insights to improve user experience, content personalization, and customer journey.
• Design and implement A/B tests and experiments to evaluate the impact of changes on user behavior and business outcomes.
• Analyze test results and provide insights to drive data-informed decision-making.
• Collaborate with cross-functional teams to translate business objectives into data-driven strategies.
• Use data insights to inform product development, content strategy, marketing campaigns, and audience targeting.
• Ensure data accuracy, integrity, and consistency by implementing data quality checks and governance processes.
• Identify data quality issues and work with relevant teams to address them.
• Stay updated on industry trends, best practices, and emerging technologies related to data analysis and visualization.Identify opportunities for process improvement and contribute to the development of data analytics capabilities within the organization.