Part‑Time Data Engineer – Remote Data Entry & Analytics Role at arenaflex
About arenaflex – Pioneering Entertainment at Scale
arenaflex is redefining how the world experiences entertainment. With more than 200 million paid members across 190+ countries, our platform delivers a vast library of series, documentaries, and feature films in dozens of languages on millions of devices. By continuously pushing the boundaries of streaming technology, we ensure that every subscriber enjoys a seamless, high‑quality viewing experience. Our mission is powered by data—every decision, from content acquisition to product innovation, is guided by insights drawn from massive, real‑time data streams.
Why This Role Matters
Data is the lifeblood of arenaflex. Our Data Engineering teams build the pipelines, models, and tools that turn raw logs into actionable intelligence. As a Part‑Time Data Engineer, you will help curate, process, and analyze data that fuels business decisions across Finance, Product, Content, and Studio divisions. This is a remote, flexible‑hours position that welcomes talent located in Mexico City as well as candidates working from anywhere within Mexico.
Role Overview
In this role you will collaborate with cross‑functional teams to design, develop, and maintain data solutions that support both batch and real‑time analytics. You will work alongside seasoned Data Engineers, Data Scientists, and product engineers to ensure that data flows reliably from ingestion to insight.
Key Responsibilities
- Design, implement, and operate scalable data pipelines using technologies such as Apache Spark and Apache Flink.
- Develop and maintain data models that enable self‑service analytics for business stakeholders.
- Write clean, production‑ready code in at least one primary language (Java, Scala, or Python) and work comfortably with SQL.
- Collaborate with product, finance, and content teams to understand data requirements and translate them into technical specifications.
- Monitor pipeline health, troubleshoot failures, and perform root‑cause analysis to improve reliability.
- Participate in code reviews, contribute to shared engineering standards, and mentor junior engineers.
- Document data schemas, pipeline architectures, and operational runbooks to ensure knowledge transfer.
- Stay current with emerging data technologies and propose improvements that enhance performance, cost‑efficiency, and scalability.
Essential Qualifications
- Proven experience (2+ years) in distributed data processing or software engineering for data services.
- Strong proficiency in at least one major programming language (Java, Scala, or Python) and solid SQL skills.
- Hands‑on experience with large‑scale data processing frameworks such as Spark or Flink.
- Demonstrated ability to work with web‑scale datasets (hundreds of terabytes or more).
- Excellent written and verbal communication skills; ability to convey technical concepts to non‑technical audiences.
- Passion for data quality, data debugging, and meticulous documentation.
- Alignment with arenaflex’s culture of candor, independence, and rapid iteration.
Preferred Qualifications
- Experience building real‑time streaming solutions (e.g., Kafka, Kinesis) that integrate with core product features.
- Background in data modeling, data warehousing, or analytics platform development.
- Familiarity with cloud platforms (AWS, GCP, Azure) and infrastructure‑as‑code tools.
- Previous work in the entertainment, media, or subscription‑based industry.
- Exposure to machine learning pipelines and feature engineering.
Skills & Competencies for Success
- Analytical Mindset: Ability to dissect complex problems, identify root causes, and propose data‑driven solutions.
- Collaboration: Comfortable partnering with product managers, analysts, and engineers across multiple time zones.
- Adaptability: Thrive in a fast‑changing environment where requirements evolve and priorities shift.
- Ownership: Take end‑to‑end responsibility for the reliability and performance of data pipelines.
- Continuous Learning: Eagerness to explore new tools, frameworks, and best practices in data engineering.
Career Growth & Learning Opportunities
arenaflex invests heavily in the professional development of its engineers. As a part‑time member of our Data Engineering team, you will have access to:
- Mentorship from senior data engineers who have built world‑class streaming infrastructure.
- Internal technical talks, workshops, and hackathons focused on big data, cloud, and machine learning.
- Opportunities to transition to full‑time roles, lead larger projects, or specialize in areas such as data science, product analytics, or infrastructure reliability.
- Funding for certifications (e.g., AWS Certified Data Analytics, Google Cloud Professional Data Engineer).
Work Environment & Culture at arenaflex
Our culture is built on a foundation of freedom and responsibility. We encourage:
- Open Feedback: Regular, candid conversations that help individuals and teams improve.
- Independent Execution: Engineers are trusted to own their work and make decisions without micromanagement.
- Diversity of Thought: A global workforce that brings varied perspectives to solve complex problems.
- Flexibility: Remote work options, flexible hours, and a results‑oriented approach that respects work‑life balance.
Compensation, Perks & Benefits
arenaflex offers a competitive, market‑aligned compensation package that includes:
- Base salary calibrated to the local market in Mexico, with adjustments for experience and skill set.
- Performance‑based bonuses tied to individual and team impact.
- Comprehensive health, dental, and vision coverage.
- Generous paid time off, parental leave, and flexible holiday policies.
- Access to a global entertainment library for personal enjoyment.
- Professional development budget, wellness programs, and employee assistance resources.
Application Process
Our interview process is designed to assess both technical expertise and cultural fit. Typical steps include:
- Screening Call: Brief conversation to discuss your background, motivations, and fit for the role.
- Technical Assessment: Coding exercise or take‑home project focused on data pipeline design.
- On‑Site (Virtual) Interviews: Deep‑dive technical discussions with senior data engineers, product partners, and a cultural interview with a hiring manager.
- Final Review: Consolidated feedback and an offer discussion.
Sample Interview Questions
- Tell me about yourself and why you’re interested in a data engineering role at arenaflex.
- Describe a challenging data pipeline you built, the obstacles you faced, and how you resolved them.
- How do you ensure data quality and reliability in large‑scale systems?
- Explain a time you collaborated with non‑technical stakeholders to deliver a data‑driven solution.
- What strategies do you use to stay current with emerging data technologies?
Why Join arenaflex?
Working at arenaflex means being part of a global entertainment leader that values data as a strategic asset. You’ll have the chance to:
- Impact millions of viewers by enabling data‑informed product decisions.
- Collaborate with world‑class engineers and analysts who are passionate about solving complex problems.
- Enjoy a flexible, remote work environment that respects your personal schedule.
- Grow your career through mentorship, training, and exposure to cutting‑edge technologies.
Ready to Make an Impact?
If you are a curious, self‑driven engineer who thrives on turning raw data into meaningful insights, we want to hear from you. Apply today and start your journey with arenaflex—where data meets entertainment, and innovation never stops.
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