Lead Data Engineer – Big Data Solutions & Cloud Warehousing – $24/hr – Full‑Time – San Francisco

About arenaflex – Pioneering Data‑Driven Experiences

arenaflex is a global leader in entertainment, media, and technology, delivering immersive experiences to millions of fans worldwide. With a legacy of storytelling excellence and a relentless focus on innovation, arenaflex blends creative vision with cutting‑edge data science to shape the future of interactive media. Our Information and Investigation group powers the next generation of web‑based features, advertising platforms, and audience‑insight tools that keep our partners, sponsors, and content creators ahead of the curve.

Why This Role Matters

As the Lead Data Engineer for arenaflex’s Commitment and Maintenance Information Designing team, you will be at the heart of a data‑centric transformation. Your work will enable the organization to harness massive data volumes, deliver real‑time analytics, and build robust data pipelines that drive strategic decisions across product, marketing, and operations. This is a unique opportunity to lead a high‑impact engineering function while collaborating with product managers, data scientists, and architects in a fast‑moving, agile environment.

Role Summary

We are seeking an experienced, highly motivated data engineering professional to design, develop, and maintain large‑scale data solutions. You will own the end‑to‑end lifecycle of data warehouses, ETL pipelines, and data models that support critical business intelligence and machine‑learning initiatives. The role demands deep technical expertise, strategic thinking, and a passion for turning raw data into actionable insights.

Key Responsibilities

• Architect & Build Scalable Data Platforms: Design and implement data warehousing solutions on both cloud (AWS, Snowflake) and on‑premise environments, ensuring high availability, fault tolerance, and performance.
• Develop Robust ETL Pipelines: Create, test, and maintain ETL processes using Hadoop, Spark, Flink, and streaming technologies to ingest, transform, and load petabyte‑scale datasets.
• Collaborate with Cross‑Functional Teams: Partner with Product Owners, Data Modelers, and Data Architects to translate business requirements into technical specifications and deliver end‑to‑end data solutions.
• Optimize Data Quality & Governance: Implement data validation, lineage, and documentation practices to uphold data integrity, compliance, and auditability.
• Performance Tuning & SLA Management: Monitor system performance, troubleshoot bottlenecks, and ensure that data services meet defined Service Level Agreements (SLAs) for latency and throughput.
• Agile Participation: Actively contribute to Scrum ceremonies, sprint planning, and retrospectives, championing continuous improvement and rapid delivery cycles.
• Mentorship & Leadership: Guide junior engineers, share best practices, and foster a culture of technical excellence and collaboration within the team.
• Documentation & Knowledge Sharing: Maintain comprehensive technical documentation, data dictionaries, and runbooks to support knowledge transfer and operational continuity.

Essential Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field (or equivalent practical experience).
• Minimum 5 years of hands‑on experience designing and operating large‑scale data platforms in a production environment.
• Proven expertise with SQL and the ability to craft performant queries across relational and analytical databases.
• Strong programming skills in Python and either Java or Scala, with a track record of building reliable data pipelines.
• Extensive experience with Hadoop ecosystem components (HDFS, Hive, Spark, PySpark) and streaming frameworks such as Apache Flink or Kafka.
• Hands‑on experience with at least one major MPP or cloud data warehouse technology (Snowflake, Amazon Redshift, Google BigQuery, etc.).
• Familiarity with data modeling concepts, dimensional modeling, and data lake architecture.
• Understanding of data integration tools and workflow orchestration platforms (e.g., Airflow, Luigi, Prefect).
• Demonstrated ability to work in Agile/Scrum environments and deliver within fast‑paced development cycles.

Preferred Qualifications & Additional Skills

• Master’s degree or advanced certifications in data engineering, cloud architecture, or big data technologies.
• Experience with AWS services such as S3, EMR, EC2, and IAM for secure, scalable data processing.
• Knowledge of containerization (Docker, Kubernetes) and infrastructure‑as‑code tools (Terraform, CloudFormation).
• Exposure to machine‑learning pipelines and collaboration with data science teams to operationalize models.
• Strong problem‑solving mindset, with the ability to diagnose complex data issues and propose elegant solutions.
• Excellent communication and stakeholder‑management skills, capable of translating technical concepts for non‑technical audiences.

Core Competencies & Personal Attributes

• Analytical Thinking: Ability to dissect large datasets, identify patterns, and drive data‑centric decision making.
• Collaboration: Team‑player who thrives in cross‑functional settings and values diverse perspectives.
• Ownership: Takes responsibility for end‑to‑end delivery, from design through production support.
• Adaptability: Comfortable navigating evolving technology stacks and shifting business priorities.
• Continuous Learning: Commitment to staying current with emerging data technologies and industry best practices.

Compensation, Benefits & Perks

arenaflex offers a competitive hourly rate of $24 per hour, complemented by a comprehensive benefits package that includes:

• Health, dental, and vision insurance with generous employer contributions.
• 401(k) retirement plan with company match.
• Paid time off, holidays, and flexible work‑hours to support work‑life balance.
• Professional development stipend for conferences, certifications, and training.
• Access to cutting‑edge technology labs and internal hackathons.
• Employee assistance programs, wellness initiatives, and on‑site amenities.

Career Growth & Learning Opportunities

At arenaflex, your career trajectory is shaped by your ambition. As a Lead Data Engineer, you will have pathways to senior technical leadership roles such as Principal Data Architect, Data Platform Manager, or Director of Data Engineering. The organization invests heavily in mentorship programs, internal mobility, and cross‑departmental projects, ensuring you gain exposure to a broad spectrum of data‑driven initiatives.

Work Environment & Culture

arenaflex fosters an inclusive, collaborative, and innovative culture where curiosity is celebrated. Our teams operate in modern, open‑plan offices in San Francisco, equipped with state‑of‑the‑art workstations, collaborative spaces, and quiet zones for focused work. We champion diversity, equity, and inclusion, and we believe that a variety of perspectives fuels creativity and better business outcomes.

Application Process

If you are ready to lead the design and delivery of world‑class data solutions at a company that blends entertainment magic with data mastery, we want to hear from you. Please submit your resume and a brief cover letter outlining your most relevant experience and why you are excited to join arenaflex.

Apply Now

Join arenaflex – Shape the Future of Data‑Powered Entertainment

At arenaflex, your work will directly influence how millions of fans experience stories, games, and interactive content. By turning raw data into strategic insight, you will help us deliver personalized, engaging experiences that keep audiences coming back for more. Take the next step in your career and become a pivotal part of a visionary team that is redefining the entertainment landscape.