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Senior Data Engineer

As a Senior Data Engineer on our Strategy & Analytics team, you will architect and optimize the data infrastructure that powers forecasting models, recommendation engines, and FAST (Free Ad-Supported Television) channel programming. This role is forward-looking and innovation-driven – you’ll leverage modern AI tools and an automation-first mindset to enhance productivity and future-proof our data stack. You will collaborate closely with firm-wide stakeholders and pave the way for future data science and AI initiatives, ensuring our cloud-based pipelines (Azure) and upcoming Snowflake data warehouse are ready to scale with emerging technologies.

Reports to: SVP, Strategy & Analytics
Exemption Status: Exempt
Pay Rate: $120k - $180k if annualized DOE
Paid Time Off: Holidays, Vacation, Paid Sick Leave, Personal Days
Compensation: Full benefits package including 401(K) with match, medical, dental, vision, and more
Work Location: Remote

KEY RESPONSIBILITIES:

• Build & Optimize Data Pipelines: Design, develop, and maintain scalable ETL/ELT pipelines on Azure to ingest, transform, and integrate data from diverse sources, supporting use cases like content forecasting, recommendation engines, and FAST channel scheduling. Ensure high data quality, reliability, and performance in all pipelines.

• AI-Augmented Development: Actively incorporate AI-assisted coding and data engineering tools (e.g., GitHub Copilot, ChatGPT) to accelerate development cycles, improve code quality, and troubleshoot complex problems. Automation-First Approach: Identify repetitive or manual data processes and streamline them through scripting, workflow automation, and AI integration to minimize manual toil and improve efficiency.

• AI/ML Infrastructure & MLOps: Lead the development of AI/ML infrastructure and pipelines – from model training to deployment – ensuring robust ML Ops practices (CI/CD for data and models, model versioning, monitoring). Build systems to deploy and serve machine learning models (e.g. forecasting or recommendation algorithms) at scale, with automated retraining and performance tracking.

• Cloud & Data Platform Management: Utilize Azure services (Data Factory, Databricks, Synapse, etc.) to manage data storage, processing, and analytics. Play a key role in the implementation of Snowflake as our cloud data warehouse – designing efficient warehouse schema, data models, and migration of data. Optimize cloud resources for cost and performance, and enforce best practices in data architecture and security.

• Innovation & Future-Proofing: Continuously evaluate and integrate emerging technologies to keep our data platform cutting-edge. Experiment with agentic LLM frameworks (e.g., LangChain, AutoGPT) to prototype autonomous data processes or intelligent agents that can interact with our data ecosystem. Explore and champion new standards like Model Context Protocol (MCP) for connecting AI models with enterprise data and context. Drive innovation to future-proof our data stack and workflows, ensuring scalability and adaptability as the studio’s data needs grow.

• Cross-Functional Collaboration: Work closely with strategy, content, and analytics teams to understand business needs and translate them into technical solutions. Partner with analysts and (future) data scientists to support their data requirements, ensuring the infrastructure can enable advanced analytics and AI model development. Provide technical mentorship and guidance to junior engineers, and promote a culture of automation, efficiency, and continuous improvement.

QUALIFICATIONS & EXPERIENCE:
• Education & Experience: Bachelor’s or Master’s in Computer Science, Data Engineering, or related field. 5+ years of experience in data engineering or similar roles, with a track record of building and managing robust data pipelines and platforms.

• Data Engineering Expertise: Proficient in Python (or Scala/Java) and SQL for data processing. Experience with big data frameworks and ETL tools. Strong knowledge of relational and NoSQL databases, data modeling, and developing data workflows in a cloud environment.

• Cloud & Warehousing: Hands-on experience with Microsoft Azure data services (such as Azure Data Factory, Databricks/Spark, Azure Functions, etc.). Familiarity with data warehousing concepts; experience with Snowflake (or similar cloud data warehouses like Redshift/BigQuery) is highly desirable, including performance tuning and best practices for cloud DW.

• AI/ML & Automation Skills: Demonstrated ability to use AI-assisted development tools (e.g., GitHub Copilot, Cursor, ChatGPT) to improve productivity and code quality. Strong automation first mindset – you naturally identify inefficiencies and craft automated solutions (using scripts, APIs, or AI) to streamline workflows. Experience with CI/CD pipelines, DevOps/DataOps, and automating testing/validation of data processes. Exposure to ML Ops tools and frameworks (e.g., MLflow, Kubeflow, Azure ML) for managing the machine learning lifecycle is a plus.

• LLM & Emerging Tech Familiarity: Enthusiasm for emerging AI technologies. Familiarity or handson experimentation with agentic LLM frameworks (such as LangChain, AutoGPT or similar) is a plus – you stay updated on how autonomous AI agents can be applied to data and analytics tasks. Knowledge of or interest in the Model Context Protocol (MCP) for managing context in LLM-based systems is also highly valued.

• Problem-Solving & Innovation: Excellent problem-solving skills with an innovative mindset. Ability to architect solutions that are future-proof, scalable, and maintainable. Eagerness to continuously learn and incorporate new tools or methodologies, especially in the AI/ML domain, to keep the data infrastructure state-of-the-art.

• Collaboration & Communication: Strong teamwork and communication skills. Proven ability to work cross-functionally with technical and non-technical stakeholders, translating strategic objectives into data engineering outcomes. Experience in an agile environment and comfort working in a fast-paced, evolving industry (media/entertainment experience is a bonus).

Join us in pushing the boundaries of analytics and data engineering through AI and automation. This role offers the opportunity to influence the future of our studio’s data strategy, implement cutting-edge technologies, and ensure that we remain at the forefront of innovation in the entertainment industry. If you are passionate about leveraging modern AI tools, automating relentlessly, and building future-proof data solutions, we encourage you to apply and help shape the next era of data-driven decision-making at Shout! Studios.

How to Apply
To apply for this position, please send in a cover letter and resume detailing your experience and interest via email to: jobs@shoutfactory.com.

Shout! Studios is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.