Senior Data Engineer

7 days ago

West Chester, PA, United States Cynet Systems Full time
Job Description:

Pay Range: $60hr - $65hr

Responsibilities:
  • Data Pipeline Development and Management: Design, construct, install, test, and maintain highly scalable data management systems. Develop and optimize ETL/ELT pipelines using PySpark and Databricks to process large volumes of structured and unstructured data.
  • Cloud Infrastructure: Utilize AWS services for data storage, computation, and orchestration, ensuring a reliable and efficient data infrastructure.
  • Data Analysis and Insights: Collaborate with business stakeholders to understand customer experience challenges and opportunities. Analyze complex datasets to identify trends, patterns, and insights related to customer behavior, network performance, product usage, and churn.
  • Business Use Case Analysis: Apply candidates analytical skills to various customer experience use cases, including:
  • Churn Prediction: Develop models to identify customers at risk of leaving and understand the underlying drivers.
  • Network Experience: Analyze network performance data to identify and address areas of poor customer experience.
  • Personalization: Enable data-driven personalization of marketing communications, offers, and customer support interactions.
  • Billing and Service Inquiries: Analyze inquiry data to identify root causes of customer confusion and drive improvements in billing and service clarity.
  • Reporting and Visualization: Create compelling and insightful reports and dashboards using Tableau or Power BI to communicate findings to both technical and non-technical audiences.
  • Data Governance and Quality: Ensure data accuracy, completeness, and consistency across all data platforms. Implement data quality checks and best practices.
  • Collaboration and Mentorship: Work closely with cross-functional teams, including product, marketing, and engineering, to deliver data-driven solutions. Mentor junior team members and promote a culture of data-driven decision-making.
Qualifications:
  • Education: Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or a related quantitative field.
  • Experience: 5+ years of experience in a data engineering or data analyst role, with a proven track record of working with large-scale data ecosystems.
  • Technical Skills:
  • Expert-level proficiency in Python and SQL.
  • Hands-on experience with PySpark for big data processing.
  • In-depth knowledge of the Databricks platform.
  • Strong experience with AWS cloud services (e.g., S3, EC2, Redshift, EMR).
  • Demonstrated expertise in data visualization and reporting with Tableau or Power BI.

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