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Lead Data Engineer – Advanced Data Architecture & Big Data Solutions (Full‑Time, $24/hr) – careerzynith
```html About careerzynith – Pioneering Data‑Driven Experiences careerzynith is a global leader in entertainment, media, and technology, delivering immersive experiences to millions of fans worldwide. Our mission is to transform storytelling through data‑powered insights, innovative platforms, and cutting‑edge analytics. As part of the careerzynith Diversion and ESPN Innovation (DE&ET) umbrella, the Information and Investigation group fuels the next generation of web‑based features, enabling partners, advertisers, and internal teams to make smarter, faster decisions. We are expanding our Commitment and Maintenance Information Designing team and are looking for a visionary Lead Data Engineer who thrives on building large‑scale data solutions, mentoring talent, and shaping the future of data architecture at careerzynith. Why This Role Matters Data is the lifeblood of every product, campaign, and strategic initiative at careerzynith. From configuring new items to measuring advertising effectiveness, our data pipelines deliver the intelligence that powers business growth. As a Lead Data Engineer, you will own the design, implementation, and continuous improvement of data warehouses, ETL processes, and analytics platforms that serve a diverse set of stakeholders across the organization. Key Responsibilities Architect & Build Scalable Data Solutions Design and develop robust data warehousing architectures that support both cloud and on‑premise environments, ensuring high availability, fault tolerance, and performance. ETL Pipeline Development Create, optimize, and maintain end‑to‑end ETL pipelines using Hadoop, Spark, AWS services, Snowflake, and other modern big‑data technologies. Collaborate with Cross‑Functional Teams Partner with Product Owners, Data Modelers, and Data Architects to translate business requirements into technical specifications and deliver production‑ready data solutions. Data Modeling & Governance Define logical and physical data models, enforce data quality standards, and document data lineage to support regulatory compliance and analytics excellence. Performance Tuning & SLA Management Monitor system performance, troubleshoot bottlenecks, and ensure that data services meet agreed‑upon Service Level Agreements (SLAs) for latency and throughput. Agile Participation Actively contribute to Scrum ceremonies, sprint planning, and retrospectives, championing continuous improvement and fostering a collaborative team culture. Mentorship & Leadership Guide junior engineers, conduct code reviews, and promote best practices in data engineering, testing, and documentation. Documentation & Knowledge Sharing Maintain comprehensive technical documentation, data dictionaries, and runbooks to facilitate knowledge transfer and operational excellence. Essential Qualifications Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field. 5+ years of hands‑on experience designing and implementing large‑scale data solutions in a fast‑paced environment. Deep expertise in SQL and the ability to craft performant queries across relational and analytical databases. Proficiency with big‑data frameworks such as Hadoop (HDFS, Hive), Spark (PySpark, Scala), and streaming platforms like Kafka or Flink. Strong programming skills in Python and either Java or Scala, with a track record of building production‑grade code. Experience with cloud data warehouses (Snowflake, Redshift, BigQuery) and cloud platforms (AWS S3, EMR, EC2, Lambda). Solid understanding of data modeling principles, dimensional modeling, and data warehousing best practices. Familiarity with data integration tools and pipeline orchestration (Airflow, Luigi, or similar). Demonstrated ability to work within Agile/Scrum frameworks and deliver incremental value. Excellent problem‑solving, analytical, and communication skills, with a customer‑first mindset. Preferred Qualifications & Additional Skills Master’s degree or advanced certifications in data engineering, cloud architecture, or related disciplines. Hands‑on experience with Snowflake’s advanced features (streams, tasks, zero‑copy cloning). Exposure to data governance tools (Collibra, Alation) and data quality frameworks. Knowledge of containerization (Docker, Kubernetes) for deploying data services. Experience in the entertainment, media, or advertising sectors, understanding the unique data challenges of these industries. Proven track record of leading technical teams, driving architectural decisions, and influencing product roadmaps. Core Skills & Competencies Technical Acumen Mastery of big‑data ecosystems, cloud services, and modern programming languages. Strategic Thinking Ability to align data solutions with business objectives and anticipate future data needs. Collaboration Strong interpersonal skills to work effectively with product, analytics, and operations teams. Leadership Mentoring mindset, fostering growth, and encouraging a culture of continuous learning. Quality Focus Commitment to data integrity, documentation, and rigorous testing. Adaptability Comfort navigating ambiguous requirements and rapidly evolving technology landscapes. Career Growth & Learning Opportunities At careerzynith, your career trajectory is shaped by ambition and curiosity. As a Lead Data Engineer, you will have direct exposure to senior leadership, influence enterprise‑wide data strategy, and gain visibility across multiple business units. We invest heavily in professional development through Sponsored certifications (AWS, Snowflake, Cloudera, etc.). Internal tech talks, hackathons, and data community meet‑ups. Mentorship programs pairing you with industry experts. Opportunities to lead high‑impact projects that drive revenue and innovation. Successful performance can lead to roles such as Data Architecture Manager, Director of Data Engineering, or Chief Data Officer within the broader careerzynith ecosystem. Compensation, Perks & Benefits careerzynith offers a competitive hourly rate of $24/hr, complemented by a comprehensive benefits package that includes Health, dental, and vision insurance with generous employer contributions. 401(k) plan with company match and financial wellness resources. Paid time off, holidays, and flexible work arrangements (including remote‑friendly policies). Employee assistance programs, mental health support, and wellness initiatives. Discounts on careerzynith entertainment experiences, merchandise, and partner services. Continuous learning stipend for courses, conferences, and certifications. Work Environment & Culture at careerzynith Our teams thrive in an inclusive, collaborative environment where creativity meets data rigor. We celebrate diversity, encourage curiosity, and empower every employee to bring their authentic self to work. The Data Engineering group operates in an open‑plan studio‑style office in San Francisco, equipped with modern workstations, breakout zones, and a vibrant community of engineers, analysts, and product innovators. Key cultural pillars include Innovation First We champion experimentation, rapid prototyping, and data‑driven decision making. Teamwork & Respect Cross‑functional collaboration is at the heart of everything we do. Growth Mindset Continuous feedback loops and learning opportunities fuel personal and professional development. Impactful Work Your contributions directly influence the experiences of millions of fans worldwide. How to Apply If you are ready to lead the design of next‑generation data platforms, mentor a talented engineering team, and make a tangible impact on a world‑class entertainment brand, we want to hear from you. Click the link below to submit your application and start your journey with careerzynith. Apply Now – Join careerzynith! Join careerzynith and Shape the Future of Data‑Powered Storytelling At careerzynith, your expertise will help power the stories that captivate audiences around the globe. We look forward to welcoming a passionate, forward‑thinking Lead Data Engineer who is eager to drive excellence, inspire teammates, and push the boundaries of what data can achieve. ``` Apply for this job
