Experienced Full Stack Data Engineer – Customer Service (L5) at arenaflex

At arenaflex, we're revolutionizing the entertainment industry with our innovative approach to storytelling and customer experience. As a leading entertainment services provider with 278 million paid memberships in over 190 countries, we're constantly pushing the boundaries of what's possible. Our Customer Service team is at the forefront of this revolution, engaging with millions of members via phone and chat in 25 different languages. As a Data Engineer (L5) in our Data Science and Analytics team, you'll play a critical role in building reliable, scalable data pipelines, transforming raw data into core business metrics, and working with custom visualization tools that surface CS insights.

The Role

arenaflex is committed to delivering an exceptional customer experience, and our Customer Service team is instrumental in making this happen. When a member has a problem using arenaflex, we want to quickly and thoroughly resolve their issue and get them back to streaming. To achieve this, we use data to rigorously measure, optimize, and personalize our Customer Service investments. Our Data Science and Engineering (DSE) team is responsible for leveraging data to drive business decisions and improve our product based on member feedback. As a Data Engineer (L5) in this role, you'll collaborate with data engineers, software engineers, and CS business owners to:

• Build reliable, scalable data pipelines using big data technologies (Hive, Presto, Spark, Flink) on medium to large-scale data sets (10s of millions of records)
• Transform raw data into core business metrics
• Work with custom visualization tools that surface CS insights
• Design structures that are adaptable to changes in the source data or business processes
• Develop advanced SQL skills and advocate for data quality
• Analyze business problems and prioritize autonomously
• Communicate effectively with analysts, engineers, and business leaders

Key Responsibilities

* Design, develop, and maintain large-scale data pipelines using big data technologies

• Collaborate with data engineers, software engineers, and CS business owners to drive business decisions
• Develop and maintain custom visualization tools to surface CS insights
• Work with data scientists to develop and maintain advanced analytics models
• Develop and maintain data quality standards and advocate for data quality
• Analyze business problems and prioritize autonomously
• Communicate effectively with analysts, engineers, and business leaders

Essential Qualifications

* At least 4 years of experience engineering data pipelines using big data technologies (Hive, Presto, Spark, Flink) on medium to large-scale data sets (10s of millions of records)

• Strong data modeling skills, with the ability to design structures that are adaptable to changes in the source data or business processes
• Strong proficiency in Python or Scala, with a passion for writing clean, supportable code
• Advanced SQL skills, with a focus on data quality and advocacy
• Analytical aptitude, with the ability to think through business problems and prioritize autonomously
• Strong communication and productive partnership with analysts, engineers, and business leaders

Preferred Qualifications

* Experience working with cloud-based data platforms (e.g. AWS, GCP, Azure)

• Experience with data warehousing and ETL tools (e.g. Informatica, Talend)
• Experience with data visualization tools (e.g. Tableau, Power BI)
• Experience with machine learning and deep learning frameworks (e.g. TensorFlow, PyTorch)
• Experience with agile development methodologies (e.g. Scrum, Kanban)

Skills and Competencies

* Strong technical skills in data engineering, data science, and software development

• Excellent analytical and problem-solving skills
• Strong communication and collaboration skills
• Ability to work in a fast-paced, dynamic environment
• Strong attention to detail and ability to prioritize tasks effectively
• Ability to adapt to changing requirements and priorities

Career Growth Opportunities and Learning Benefits

arenaflex is committed to helping our employees grow and develop their careers. As a Data Engineer (L5), you'll have opportunities to:

• Work on high-impact projects that drive business decisions and improve our product
• Collaborate with cross-functional teams to drive innovation and growth
• Develop your technical skills and expertise through training and mentorship programs
• Participate in hackathons and innovation challenges to showcase your creativity and problem-solving skills
• Attend industry conferences and events to stay up-to-date on the latest trends and technologies

Work Environment and Company Culture

arenaflex is a unique culture and environment that values diversity, inclusion, and innovation. We're committed to creating a workplace that's inclusive, supportive, and empowering. As a Data Engineer (L5), you'll be part of a team that's passionate about delivering exceptional customer experiences and driving business growth.

Compensation, Perks, and Benefits

arenaflex offers a comprehensive compensation package that includes:

• An annual salary, with the option to choose how much of your compensation you want in salary versus stock options
• Comprehensive benefits, including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits
• Paid leave of absence programs, including vacation, holidays, and sick paid time off
• Flexible time off, with the option to take time off as needed
• Opportunities for professional development and growth, including training and mentorship programs

Conclusion

If you're a talented Data Engineer with a passion for delivering exceptional customer experiences and driving business growth, we want to hear from you. Join our team at arenaflex and be part of a revolution that's changing the face of entertainment. Apply now and take the first step towards an exciting new career opportunity. Apply Job! Apply for this job