Senior Data and Analytics Engineering Manager

Senior Data and Analytics Engineering Manager

Radial Entertainment is the largest independent, ad‑supported streaming network and film/TV distributor worldwide. We’re looking for a skilled and ambitious Sr. Data and Analytics Engineering Manager to lead the expansion of our modern, extensible platform of data pipelines, orchestrations, and analytics infrastructure into an exciting new phase. This role blends technical leadership with hands‑on development, playing a central role in the design and implementation of scalable data models, high‑quality transformations, and observability tooling across our cloud‑native stack.

You’ll collaborate closely with stakeholders across BI, data science, and business teams to ensure the delivery of reliable, analytics‑ready data — powering everything from machine learning models to reporting derived from partner streaming platforms, third‑party market data, and first‑party app and operational sources. You’ll be a leader in integrating best practices around state‑of‑the‑art AI developer tools and architecture into our workflows — from code generation to feature engineering and intelligent agents — ensuring the team is equipped to move faster, build smarter, and stay at the forefront of innovation.

Reporting to the Director of Data Product, you’ll help define and evolve best practices across engineering, developer experience, and automation — shaping the next phase of our platform’s growth and intelligence.

Department: Content Investment & Business Intelligence

Reports to: VP of Data Product

Exemption Status: Exempt

Pay Rate: $150k - $175k 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 (must reside in Los Angeles or New York), optional hybrid available if LA-based

• Manage and grow our data/analytics engineering function, serving as both a day‑to‑day technical lead and a manager of engineers
• Work with variety of teams to onboard data and support an expanding suite of reporting, advanced analytic and operational capabilities
• Evolve Data Warehouse schema in accordance with modeling best practices for appropriate analytic and operational use‑cases
• Maintain and expand core ELT orchestrations with an emphasis on augmenting data observability and controls across different layers of our modern data stack
• Implement automated tests and QA processes to ensure the quality and reliability of all contributions
• Collaborate with data science stakeholders to ensure platform supports robust feature engineering and selection across machine learning methodologies
• Synergize contributions with greater dev team and help support best practices for efficient Dev Ops

• 4‑7 years of relevant work experience in data intensive applications, preferably around high volume streaming data, audience analytics, ads data
• 3+ years as an individual contributor / maintainer of batch, streaming pipelines + orchestrations in a data warehousing or data science context
• Proficiency in one general purpose programming language, preferably python, as well as experience scripting in bash and configuring infra
• Strong Experience with Cloud Data tooling (AWS preferred)
• Demonstrated experience integrating and orchestrating containerized workflows / applications (ECS, EKS)
• Strong foundations in data modeling techniques, (dimensional, object, app access patterns) and transformations (DBT preferred)
• Expert SQL skills writing/tuning complex, efficient analytic queries against MPP database (Snowflake)
• Strong Development lifecycle fundamentals: automated testing (pytest, selenium, bandit), CI/CD (Gitlab, git), agile estimation and planning
• Familiarity with Tableau or similar BI data interfaces, architecture, optimizations, visuals
• Experience integrating or experimenting with AI‑augmented development workflows (Cursor, Copilot, etc.) and enthusiasm for generative AI infrastructure (RAG, agents, context management, observability)
• Ability to balance technical leadership with hands‑on feature development where needed
• Ability to…