About careerzynith
careerzynith is a global leader in entertainment, media, and technology, delivering unforgettable experiences to millions of fans worldwide. With a heritage of storytelling excellence and a relentless focus on innovation, careerzynith blends creative passion with cutting‑edge data science to drive business growth, enhance customer engagement, and unlock new revenue streams. Our remote‑first culture empowers talented professionals to work from anywhere in the United States while staying connected to a vibrant, collaborative community of engineers, analysts, and creators.
Why This Role Matters
As a Senior Data Engineer within the Product Execution and Instrumentation Group at careerzynith, you will be at the heart of a data‑driven transformation. Your work will enable the seamless flow of information across the entire product lifecycle—from ingestion and onboarding to analytics and insight delivery—supporting critical decision‑making for our portfolio of iconic brands. This is a unique opportunity to shape a next‑generation data platform that powers everything from content recommendation engines to operational dashboards, all while leveraging industry‑leading technologies such as AWS, Snowflake, Databricks, and Delta Lake.
Key Responsibilities
- Design, build, and maintain high‑performance data pipelines in Scala, Python, and PySpark that process terabytes of data daily, ensuring 99.9% uptime and adherence to Service Level Agreements (SLAs).
- Architect and evolve a Lakehouse‑driven data platform, collaborating with product owners, data scientists, and analytics engineers to migrate legacy workloads to a modern, unified environment.
- Develop robust ETL/ELT solutions that operate seamlessly across hybrid environments (cloud, on‑premise, and multi‑cloud), leveraging AWS services (S3, EMR, EC2) and Snowflake’s elastic compute.
- Partner with Data Product Managers, Data Architects, and Business Intelligence teams to translate business requirements into scalable technical designs.
- Maintain comprehensive documentation, data lineage, and metadata catalogs to support data governance, quality, and compliance initiatives.
- Drive continuous improvement by identifying automation opportunities, optimizing cost, and implementing best practices for data security and reliability.
- Participate actively in Agile ceremonies (Scrum, Sprint Planning, Retrospectives) and champion a culture of collaboration, knowledge sharing, and rapid iteration.
- Mentor junior engineers, conduct code reviews, and foster a learning environment that encourages curiosity and technical excellence.
- Engage directly with internal stakeholders—product managers, marketing analysts, and finance partners—to understand pain points and deliver data‑centric solutions that create measurable business impact.
Essential Qualifications
- Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, or a related discipline (or equivalent professional experience).
- 5+ years of hands‑on experience building large‑scale data pipelines using Scala, Python, and PySpark.
- Deep expertise in SQL and the ability to craft performant queries for complex analytical workloads.
- Proven track record with cloud data platforms—particularly AWS (S3, EMR, EC2) and at least one MPP or cloud data warehouse technology such as Snowflake, Redshift, or BigQuery.
- Strong foundation in data modeling, data warehousing, and Lakehouse concepts, including experience with Delta Lake and Databricks.
- Solid understanding of data streaming technologies (e.g., Kafka) and real‑time processing frameworks.
- Experience working in Agile environments, with familiarity in Scrum and Kanban practices.
- Excellent communication and interpersonal skills, with the ability to influence cross‑functional teams and articulate technical concepts to non‑technical audiences.
Preferred Qualifications & Additional Skills
- Master’s degree or advanced certifications in data engineering, cloud architecture, or related fields.
- Hands‑on experience with Snowflake performance tuning, clustering, and materialized views.
- Knowledge of containerization (Docker, Kubernetes) and CI/CD pipelines for data workloads.
- Familiarity with data governance frameworks (e.g., GDPR, CCPA) and data catalog tools.
- Background in the media, entertainment, or streaming industry, providing context for content‑driven data challenges.
- Demonstrated ability to lead technical initiatives, drive architectural decisions, and mentor high‑performing engineering teams.
Core Skills & Competencies
- Analytical Thinking: Ability to break down complex problems, design elegant solutions, and evaluate trade‑offs.
- Collaboration: Strong team player who thrives in a distributed environment, building trust with peers across geography.
- Ownership: Proactive mindset with a focus on delivering end‑to‑end solutions and taking responsibility for production stability.
- Adaptability: Comfortable navigating fast‑changing priorities and emerging technologies.
- Continuous Learning: Commitment to staying current with industry trends, open‑source projects, and best practices.
Compensation, Benefits & Perks
careerzynith offers a competitive salary range of $35,000 – $40,000 per year (adjusted for experience and location) along with a comprehensive benefits package that includes:
- Health, dental, and vision insurance with generous employer contributions.
- 401(k) plan with company match.
- Paid time off, holidays, and flexible work schedules to support work‑life balance.
- Remote‑work stipend for home office setup, high‑speed internet, and ergonomic equipment.
- Professional development budget for conferences, certifications, and online courses.
- Employee assistance program, wellness initiatives, and mental‑health resources.
- Opportunities to participate in internal hackathons, innovation labs, and cross‑functional projects.
Career Growth & Learning Opportunities
At careerzynith, your career trajectory is shaped by your ambition. As a Senior Data Engineer, you will have pathways to advance into:
- Lead Data Engineer or Data Platform Architect roles, overseeing multi‑team initiatives.
- Data Product Management, influencing product strategy with data‑driven insights.
- Technical leadership positions such as Engineering Manager or Director of Data Engineering.
- Specialized tracks in Machine Learning Engineering, Data Science, or Cloud Architecture.
Our learning culture is reinforced through regular tech talks, mentorship programs, and access to a rich library of resources. You will work alongside industry experts who are passionate about pushing the boundaries of data technology.
Work Environment & Culture at careerzynith
careerzynith embraces a remote‑first philosophy, trusting employees to deliver results wherever they feel most productive. Our culture is built on three pillars:
- Creativity: We celebrate innovative thinking and encourage you to experiment with new tools and approaches.
- Collaboration: Transparent communication channels, virtual coffee chats, and cross‑team initiatives keep us connected.
- Integrity: Ethical data handling, respect for privacy, and a commitment to inclusive practices guide every decision.
Whether you are joining a tight‑knit squad of data engineers or collaborating with global product teams, you will experience a supportive environment that values diversity, equity, and inclusion.
How to Apply
If you are ready to make an impact on a world‑class entertainment brand, drive data‑centric innovation, and grow your career in a forward‑thinking organization, we want to hear from you. Click the link below to submit your application and become part of the careerzynith family.
Apply Now – Join careerzynith
Closing Statement
careerzynith is committed to building a workforce that reflects the audiences we serve. We encourage candidates of all backgrounds to apply. Your expertise, curiosity, and passion for data will help us shape the future of entertainment. Take the next step in your career—apply today and help us turn data into unforgettable experiences.
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