About skillspath
skillspath is a global leader in entertainment‑driven technology solutions, delivering immersive digital experiences to millions of users worldwide. With a heritage rooted in storytelling and a forward‑looking focus on data‑centric innovation, skillspath empowers its partners—ranging from media giants to emerging content creators—to unlock insights, accelerate product development, and drive revenue growth. Our Information and Investigation group, part of the skillspath Web‑Based Features division, operates at the intersection of big data, cloud engineering, and advanced analytics, building the platforms that power the next generation of interactive entertainment.
Why This Role Matters
Data is the lifeblood of skillspath’s digital ecosystem. From configuring new product features to measuring advertising effectiveness, from supporting internal stakeholders to enabling external partners, every decision is driven by high‑quality, timely information. As a Lead Data Engineer, you will own the design, implementation, and optimization of large‑scale data solutions that serve critical business functions across the organization. Your work will directly influence the speed at which new experiences reach our audience, the accuracy of our analytics, and the overall reliability of our data platform.
Key Responsibilities
- Architectural Design: Lead the design and evolution of data products and data warehouses that support skillspath’s Commitment and Maintenance Investigation and Data Science initiatives.
- Data Pipeline Development: Build, maintain, and scale robust ETL pipelines in massive data environments (cloud, on‑premises, hybrid), ensuring data is ingested, transformed, and delivered with high reliability.
- Technology Stack Management: Leverage Hadoop, AWS, Snowflake, Flink, and Kafka, writing production‑grade code in Python, Scala, and Java to process petabyte‑scale datasets.
- Data Modeling & Governance: Collaborate with Data Product Owners, Data Modelers, and Data Architects to define data models, enforce data quality standards, and document lineage for the core data lake and downstream warehouses.
- Performance Optimization: Continuously monitor and tune data solutions to meet stringent SLAs, guaranteeing low latency, high throughput, and cost‑effective resource utilization.
- Agile Collaboration: Participate actively in Scrum ceremonies, championing continuous improvement, sprint planning, and retrospectives to enhance team velocity and product quality.
- Documentation & Knowledge Sharing: Produce clear, detailed documentation of architecture decisions, pipeline configurations, and operational procedures to support data stewardship and onboarding.
- Mentorship: Guide junior engineers, fostering a culture of learning, curiosity, and technical excellence within the data engineering team.
Essential Qualifications
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical field (or equivalent practical experience).
- 5+ years of hands‑on experience designing and operating large‑scale data platforms in a fast‑paced, production environment.
- Deep expertise with SQL and the ability to craft performant queries across distributed data stores.
- Proven experience with big‑data frameworks such as Hadoop (HDFS, Hive, Impala, PySpark) and real‑time streaming technologies like Apache Flink or Kafka.
- Strong programming skills in Python and either Java or Scala, with a track record of delivering clean, maintainable code.
- Hands‑on experience with at least one major MPP or cloud data‑warehouse technology (e.g., Snowflake, Redshift, BigQuery, Azure Synapse).
- Familiarity with data‑pipeline orchestration tools (e.g., Airflow, Prefect) and data‑quality frameworks.
- Solid understanding of data modeling principles, dimensional modeling, and data‑warehouse best practices.
- Experience working in Scrum or other Agile methodologies, with a focus on delivering incremental value.
Preferred Qualifications & Nice‑to‑Have Skills
- Master’s degree or advanced certifications in data engineering, cloud architecture, or related disciplines.
- Hands‑on experience with AWS services such as S3, EMR, EC2, Lambda, and Glue.
- Exposure to machine‑learning pipelines and collaboration with data‑science teams to operationalize models.
- Knowledge of data‑privacy regulations (GDPR, CCPA) and best practices for secure data handling.
- Experience with infrastructure‑as‑code tools (Terraform, CloudFormation) to provision and manage cloud resources.
- Demonstrated ability to troubleshoot complex data issues, perform root‑cause analysis, and implement long‑term fixes.
Core Skills & Competencies
- Analytical Thinking: Ability to dissect complex problems, identify patterns, and propose data‑driven solutions.
- Communication: Clear articulation of technical concepts to both technical and non‑technical stakeholders.
- Collaboration: Strong team player who thrives in cross‑functional environments, building trust with product, analytics, and operations teams.
- Adaptability: Comfortable navigating a rapidly evolving technology landscape and embracing new tools and methodologies.
- Ownership: Proactive mindset with a sense of responsibility for the end‑to‑end health of data products.
Career Growth & Learning Opportunities
skillspath invests heavily in the professional development of its employees. As a Lead Data Engineer, you will have access to:
- Mentorship from senior architects and industry thought leaders.
- Sponsored certifications (AWS Certified Solutions Architect, SnowPro, etc.) and tuition reimbursement for advanced degrees.
- Internal hackathons, data‑innovation challenges, and cross‑team projects that broaden your skill set.
- Opportunities to transition into senior leadership roles such as Data Platform Manager, Director of Data Engineering, or Chief Data Officer.
Work Environment & Culture at skillspath
Our San Francisco office blends modern collaborative spaces with quiet zones for focused work. We champion a culture of inclusion, creativity, and continuous improvement. Key cultural pillars include:
- Innovation First: We encourage experimentation and reward ideas that push the boundaries of entertainment technology.
- People‑Centric: Flexible work hours, remote‑work options, and generous paid time off support work‑life harmony.
- Diversity & Inclusion: A commitment to building a workforce that reflects the global audience we serve.
- Health & Well‑Being: Comprehensive medical, dental, and vision plans, on‑site wellness programs, and mental‑health resources.
Compensation, Perks & Benefits
skillspath offers a competitive hourly rate of $24 per hour, complemented by a robust benefits package that includes:
- Performance‑based bonuses and equity participation.
- Full‑coverage health, dental, and vision insurance for employees and dependents.
- 401(k) retirement plan with company match.
- Generous paid parental leave and family‑care assistance.
- Professional development stipend, conference attendance, and access to an extensive learning library.
- Free meals, snacks, and beverages in the office, plus a transportation stipend for commuting.
How to Apply
If you are passionate about building world‑class data infrastructure, thrive in a fast‑moving entertainment technology environment, and are ready to lead a talented engineering team, we want to hear from you. Submit your resume and a brief cover letter highlighting your most relevant experience through the link below.
Apply Now – Join skillspath Today!
Closing Statement
skillspath is more than a workplace; it’s a launchpad for innovators who want to shape the future of digital entertainment. By joining our data engineering team, you will play a pivotal role in turning raw data into actionable insights that delight audiences worldwide. Take the next step in your career—apply today and become a catalyst for data‑driven storytelling at skillspath.
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