Senior Data Analyst – Remote Data Entry & Virtual Assistant Specialist for arenaflex Streaming Services

About arenaflex – Shaping the Future of Entertainment

arenaflex is a global leader in streaming entertainment, delivering beloved stories and cutting‑edge content to millions of households worldwide. Our portfolio spans multiple streaming platforms, offering a diverse range of movies, series, live sports, and original productions. As part of the arenaflex family, you will join a dynamic, fast‑growing team that thrives on creativity, data‑driven decision making, and a relentless focus on the fan experience. We are committed to fostering an inclusive culture where curiosity, collaboration, and continuous learning are celebrated.

Why This Role Matters

The Senior Data Analyst position is a cornerstone of our Subscriber Insights function. You will partner with cross‑functional teams to ensure the accurate capture, transformation, and delivery of subscriber data that powers critical business decisions across the arenaflex streaming ecosystem. Your work will directly influence subscription growth, churn mitigation, and the delivery of personalized experiences to our audience.

Key Responsibilities

• Data Acquisition & Archival: Own the end‑to‑end process for ingesting, validating, and archiving subscriber data related to subscription changes, plan migrations, and new user onboarding.
• Issue Identification & Remediation: Detect data anomalies, flag impacted subscribers, and collaborate with the Incident Management team to ensure timely remediation and accurate communication.
• Business Requirement Translation: Work closely with product, finance, and operations stakeholders to translate business needs into clear technical specifications and data delivery schedules.
• Data Quality & Governance: Build and maintain robust data models that support reliable subscriber metrics, ensuring consistency across reporting layers.
• Project Coordination: Lead project timelines, coordinate cross‑functional handoffs, and guarantee readiness for major product launches or promotional events.
• Process Improvement: Drive alignment between Data Engineering, Business Operations, and Finance by establishing standardized communication protocols and playbooks.
• Collaboration with Data Product & Quality Teams: Contribute to the design of resilient data pipelines that minimize incidents and improve overall data reliability.
• Stakeholder Communication: Provide concise executive summaries, visual dashboards, and actionable insights to senior leadership and partner teams.

Essential Qualifications

• Minimum 2 years of hands‑on experience developing SQL queries and managing ETL pipelines in a production environment.
• At least 2 years of analytical experience interpreting complex data sets to drive business outcomes.
• Proficiency in a statistical programming language such as Python or R, with the ability to script data transformations and perform exploratory analysis.
• Familiarity with data visualization and BI tools (e.g., Looker, Tableau, Power BI, or Chartio).
• Strong relational skills, coupled with excellent written and verbal communication abilities.
• Demonstrated capability to convey technical concepts to non‑technical audiences, tailoring the message to diverse stakeholder groups.

Preferred Qualifications & Nice‑to‑Haves

• Advanced degree (Master’s or Ph.D.) in Data Science, Statistics, Computer Science, or a related field.
• Experience with statistical testing methodologies, regression analysis, and hypothesis‑driven experimentation.
• Knowledge of data streaming technologies such as Apache Kafka or AWS Kinesis.
• Exposure to cloud‑based data warehousing solutions (e.g., Snowflake, Redshift, BigQuery).
• Understanding of subscription‑based business models and key performance indicators (KPIs) such as ARPU, LTV, churn rate, and conversion funnels.

Core Skills & Competencies

• Analytical Mindset: Ability to dissect large data sets, identify patterns, and translate findings into strategic recommendations.
• Problem‑Solving: Proactive approach to troubleshooting data issues, root‑cause analysis, and implementing preventive measures.
• Collaboration: Comfortable working in a matrixed environment, building strong relationships with product managers, engineers, finance analysts, and senior leadership.
• Attention to Detail: Commitment to data accuracy, consistency, and integrity across all reporting layers.
• Communication: Strong storytelling ability, using data visualizations and clear narratives to influence decision‑making.
• Adaptability: Thrive in a fast‑paced, ever‑changing streaming landscape, balancing multiple priorities and tight deadlines.

Career Growth & Learning Opportunities

At arenaflex, your professional development is a priority. As a Senior Data Analyst, you will have access to:

• Mentorship from senior data leaders and industry experts.
• Continuous learning stipends for certifications, conferences, and online courses.
• Opportunities to lead high‑impact projects that shape the future of streaming entertainment.
• Clear career pathways toward roles such as Data Science Lead, Analytics Manager, or Product Analytics Director.
• Cross‑functional exposure to product strategy, finance, and engineering, broadening your business acumen.

Work Environment & Culture at arenaflex

Our remote‑first philosophy empowers you to work from anywhere in the United States while staying connected to a vibrant, collaborative community. We champion:

• Inclusivity: A diverse workforce where every voice is heard and valued.
• Innovation: A culture that encourages experimentation, data‑driven risk‑taking, and continuous improvement.
• Work‑Life Balance: Flexible schedules, generous paid time off, and wellness programs to support mental and physical health.
• Team Spirit: Regular virtual coffee chats, hackathons, and knowledge‑sharing sessions that foster camaraderie.

Compensation, Perks & Benefits

arenaflex offers a competitive hourly rate ranging from $20–$30 per hour**, commensurate with experience and expertise. In addition to base compensation, you will enjoy: