About talentnexus – Pioneering the Future of Streaming Entertainment
talentnexus is a global leader in streaming entertainment, delivering beloved content to millions of households worldwide. Our mission is to blend cutting‑edge technology with compelling storytelling, creating unforgettable experiences for viewers on any device. At the heart of this mission lies data – the engine that powers content strategy, pricing models, advertising effectiveness, and audience engagement. As a member of the talentnexus Streaming Services (ASS) team, you will join a vibrant community of innovators who turn raw data into actionable insights that shape the future of entertainment.
Based in the tech‑rich hub of San Francisco, CA, our Information & Analytics group collaborates closely with product, engineering, and business partners across the organization. We are looking for a seasoned Lead Data Engineer who can architect, build, and scale data solutions that empower every stakeholder to make smarter, faster decisions. If you thrive in a fast‑moving, data‑centric environment and are eager to influence the next generation of streaming experiences, this role is your gateway to impact.
Key Responsibilities
As the Lead Data Engineer, you will own the end‑to‑end lifecycle of data products that drive critical business outcomes. Your day‑to‑day responsibilities include:
- Data Product Development: Design, develop, and evolve data products and warehouses that support customer‑engagement analytics, retention modeling, and advanced data‑science initiatives.
- ETL Pipeline Architecture: Build robust, scalable ETL (Extract, Transform, Load) pipelines for massive data volumes across cloud, on‑premises, and hybrid environments.
- Data Architecture & Modeling: Craft logical and physical data models, define data marts, and implement best‑in‑class data‑warehouse patterns that ensure high performance and reliability.
- Cross‑Functional Collaboration: Partner with data product managers, data architects, data scientists, and software engineers to translate business requirements into technical solutions.
- Documentation & Governance: Maintain comprehensive documentation of data flows, lineage, and metadata while enforcing data‑quality standards and governance policies.
- Operational Excellence: Monitor, troubleshoot, and optimize data pipelines to meet stringent Service Level Agreements (SLAs) and support mission‑critical analytics workloads.
- Agile Delivery: Actively participate in Scrum ceremonies, sprint planning, and retrospectives to foster continuous improvement and rapid delivery.
- Mentorship & Leadership: Guide junior engineers, share best practices, and champion a culture of technical excellence and knowledge sharing.
Essential Qualifications
To succeed in this role, you should demonstrate a strong foundation across the following areas:
- SQL Mastery: Ability to write complex, performant SQL queries, optimize execution plans, and build reusable data sets for analytics consumption.
- Distributed Systems Experience: Hands‑on expertise with big‑data frameworks such as Apache Spark, Hadoop ecosystem components (HDFS, Hive, Impala), and familiarity with PySpark or Scala for large‑scale data processing.
- Programming Proficiency: Advanced coding skills in Python and either Java or Scala, enabling you to develop production‑grade data pipelines and utilities.
- MPP/Cloud Data Warehouses: Practical experience with at least one massively parallel processing or cloud‑native warehouse technology (e.g., Snowflake, Amazon Redshift, Google BigQuery).
- Data Integration Tools: Proven ability to design, implement, and maintain workflow orchestration using Apache Airflow or comparable platforms.
- Data Modeling & Warehousing: Deep understanding of dimensional modeling, star/snowflake schemas, and data‑lake architecture patterns.
- Agile Methodology Familiarity: Comfortable working within Scrum or Kanban frameworks, delivering incremental value each sprint.
- Analytical & Communication Skills: Strong problem‑solving mindset, meticulous attention to detail, and the ability to convey technical concepts to non‑technical stakeholders.
Preferred Experience & Nice‑to‑Have Skills
- Hands‑on experience with Amazon Web Services (AWS) services such as S3, EMR, EC2, and Lambda.
- Exposure to containerization technologies (Docker, Kubernetes) for deploying data workloads.
- Knowledge of streaming data platforms like Apache Kafka or Kinesis.
- Familiarity with data‑governance frameworks (e.g., Apache Atlas, Collibra) and data‑privacy regulations (GDPR, CCPA).
- Experience mentoring teams in a fast‑growth, high‑scale environment.
Core Skills & Competencies
- Technical Leadership: Ability to set technical direction, evaluate emerging technologies, and drive architectural decisions.
- Problem Solving: Systematic approach to diagnosing complex data issues and delivering root‑cause solutions.
- Collaboration: Strong team player who builds trust across product, engineering, and business domains.
- Adaptability: Comfortable navigating ambiguous requirements and rapidly shifting priorities in a dynamic industry.
- Continuous Learning: Commitment to staying current with data‑engineering trends, cloud services, and best practices.
Career Growth & Learning Opportunities
talentnexus invests heavily in the professional development of its people. As a Lead Data Engineer, you will have access to:
- Mentorship from senior architects and industry thought leaders.
- Sponsored certifications (e.g., AWS Certified Data Analytics, SnowPro Core).
- Internal hackathons and innovation labs where you can prototype cutting‑edge data solutions.
- Cross‑functional rotation programs that expose you to product management, machine learning, and business analytics.
- Clear promotion pathways from Lead Engineer to Principal Engineer, Data Platform Manager, or Director of Data Engineering.
Work Environment & Culture at talentnexus
Our San Francisco office blends modern design with collaborative spaces, offering a vibrant atmosphere that encourages creativity and knowledge sharing. Key cultural pillars include:
- Data‑Driven Decision Making: Every product and strategy is backed by rigorous analytics.
- Innovation First: We empower teams to experiment, fail fast, and iterate.
- Inclusivity & Belonging: Diverse perspectives are celebrated, and every voice matters.
- Work‑Life Harmony: Flexible work hours, generous paid time off, and remote‑work options when appropriate.
- Community Impact: Opportunities to contribute to social responsibility initiatives and industry‑wide open‑source projects.
Compensation, Perks & Benefits
talentnexus offers a competitive compensation package designed to attract top talent:
- Hourly Rate: $24 per hour, reflecting market‑aligned remuneration for senior data‑engineering expertise.
- Performance Bonuses: Annual incentive programs tied to individual and company performance.
- Health & Wellness: Comprehensive medical, dental, and vision coverage, plus mental‑health resources.
- Retirement Savings: 401(k) plan with generous employer matching.
- Learning Stipends: Annual budget for conferences, courses, and certifications.
- Technology Allowance: Home‑office equipment and software subscriptions to support remote productivity.
- Employee Assistance Programs: Resources for financial planning, counseling, and family support.
How to Apply
If you are passionate about big data, love solving complex engineering challenges, and want to shape the future of streaming entertainment, we want to hear from you. Submit your application today and become a pivotal part of talentnexus’s data‑driven journey.
Apply Now – Join the talentnexus Streaming Services Team!
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