Why Join remotehirings?
remotehirings is a global leader in streaming entertainment, delivering premium video content to millions of households worldwide. With a portfolio that spans blockbuster movies, award‑winning series, live sports, and exclusive originals, remotehirings has redefined how audiences experience storytelling. As the industry continues to evolve, remotehirings invests heavily in data‑driven decision making, innovative technology, and a culture that champions creativity, collaboration, and continuous learning.
Our Remote Data Entry & Subscriber Insight team plays a pivotal role in ensuring the accuracy, timeliness, and strategic relevance of subscriber data across all remotehirings streaming services, including remotehirings+, remotehirings Stream, remotehirings Sports+, and remotehirings Star+. If you thrive in fast‑paced environments, love turning raw data into actionable insights, and enjoy the flexibility of remote work, this is the next step in your career.
Position Overview
As a Senior Data Analyst – Remote Data Entry & Subscriber Insight Specialist at remotehirings, you will lead the end‑to‑end subscriber data pipeline. You’ll partner with cross‑functional teams to capture, validate, and transmit critical subscriber changes—such as subscription upgrades, plan migrations, and new data captures—ensuring that our business stakeholders have reliable data for revenue forecasting, product planning, and customer experience optimization.
Key Responsibilities
- Data Collection & Validation: Oversee the intake and documentation of subscriber information related to pricing changes, plan migrations, and new data captures. Ensure data accuracy and compliance with internal policies and regulatory requirements.
- Stakeholder Collaboration: Work closely with upstream data partners, product owners, Business Operations, and Finance to align on data definitions, timing, and delivery mechanisms.
- Issue Identification & Resolution: Detect and flag subscribers impacted by system incidents or required remediation actions. Coordinate timely fixes to guarantee that eligible customers receive appropriate discounts or credits.
- Documentation & Communication: Translate complex business requirements into clear technical specifications. Produce concise status updates and roadblock summaries for senior leadership and cross‑functional teams.
- Data Architecture Support: Contribute to the design and maintenance of robust data models that underpin subscriber analytics, ensuring scalability and performance across high‑volume streaming services.
- Project Management: Lead project timelines, manage cross‑functional deliverables, and communicate progress against critical business milestones such as quarterly revenue close and new product launches.
- Process Improvement: Champion best practices for data ingestion, quality assurance, and communication handbooks, driving standardization across Data, Business Operations, and Finance.
- Analytics Enablement: Partner with Data Product and Data Quality teams to develop analytical solutions that surface actionable insights for product, marketing, and retention strategies.
Essential Qualifications
- Minimum 3+ years of professional experience building and maintaining ETL pipelines using SQL, with a focus on high‑throughput data environments.
- At least 3+ years of hands‑on experience in a data‑focused role such as Data Analyst, Data Engineer, or Business Intelligence specialist.
- Proficiency in a statistical programming language (Python or R) for data manipulation, transformation, and analysis.
- Familiarity with data visualization and BI tools such as Tableau, Looker, or Chartio to create dashboards that inform business decisions.
- Strong analytical mindset with the ability to translate business requirements into technical implementations and communicate insights to both technical and non‑technical audiences.
- Excellent written and verbal communication skills, combined with a collaborative approach to problem solving.
- Bachelor’s degree in a quantitative discipline (Computer Science, Engineering, Mathematics, Statistics, Economics, etc.).
Preferred (Nice‑to‑Have) Qualifications
- Advanced knowledge of statistical concepts such as hypothesis testing, regression analysis, and predictive modeling.
- Master’s degree or other postgraduate qualifications in a related field.
- Experience with data streaming platforms (e.g., Apache Kafka, AWS Kinesis) and real‑time data processing.