Sr Analytics Engineer

Sr. Analytics Engineer at Philo — Research Report

Introduction

The Sr. Analytics Engineer role at Philo offers a prime chance to shape data strategies for a fast-growing streaming service. For the upcoming season, this remote or hybrid position in New York, NY, blends advanced analytics with real business impact. It's a career accelerator, building skills that top tech firms crave while working on products millions use daily.

Overview of Philo

Philo delivers live TV streaming at an affordable price, focusing on entertainment, news, and sports channels without bloated cable packages. Launched in 2015, it targets cord-cutters with a skinny bundle of 70+ channels, including AMC, HGTV, and Discovery, for just $28 monthly.

In the crowded streaming market, Philo carves a niche against Hulu + Live TV, Sling TV, and YouTube TV by emphasizing simplicity and low cost. Its multichannel video programming distributor (MVPD) model aggregates popular networks, boasting over 3 million subscribers as of 2023 with steady growth fueled by word-of-mouth and partnerships.

Key products include the Philo app for iOS, Android, Roku, and smart TVs, plus DVR features with unlimited recordings. Recent expansions added sports tiers and on-demand libraries, driving user engagement metrics up 25% year-over-year.

Philo's culture thrives on innovation and efficiency, with a remote-first vibe that attracted talent during the pandemic. Employees rave about collaborative teams, unlimited PTO, and a flat hierarchy where ideas from juniors influence roadmaps—Glassdoor rates it 4.5/5 for work-life balance.

People flock to Philo for its startup energy in a mature industry, offering equity upside and exposure to high-scale data challenges. It's ideal for analytics pros wanting to impact consumer tech without Big Tech bureaucracy.

Sr. Analytics Engineer Role

Role Overview

Sr. Analytics Engineers at Philo build scalable data pipelines and models to optimize streaming performance and user retention. You'll turn raw viewer data into actionable insights, directly influencing product features like personalized recommendations. This role drives millions in revenue by reducing churn and boosting ad efficiency.

Detailed Responsibilities

• Design and maintain ETL pipelines using dbt and Airflow to process petabytes of streaming logs.
• Develop A/B tests and causal models in Python to evaluate features like channel surfacing.
• Build dashboards in Looker for real-time metrics on viewer engagement and acquisition costs.
• Collaborate with product managers to forecast subscriber growth using time-series analysis.
• Optimize SQL queries on Snowflake for sub-second latency in executive reporting.
• Conduct deep dives into funnel drop-offs, recommending UI tweaks that lift retention by 5-10%.
• Mentor junior engineers on best practices for data quality and schema evolution.

Day-to-Day Workflow

Mornings kick off with Slack standups reviewing overnight metrics, like peak-hour buffering rates. You'll spend mid-morning refining pipelines or querying terabytes of user events to spot anomalies. Afternoons involve cross-team syncs with product and engineering, prototyping models, and iterating on Looker viz based on feedback.

Expect ad-hoc fires, like debugging a spike in session abandons, balanced by deep projects like ML-based churn prediction. Weekly, you'll present insights in all-hands, ensuring your work ties to OKRs like 90%+ viewer satisfaction.

Tools and Technologies

• Data Warehousing: Snowflake, BigQuery for scalable storage.
• Orchestration: Airflow, dbt for transformations.
• Querying: SQL (advanced), Python (Pandas, NumPy, Scikit-learn).
• Visualization: Looker, Tableau for interactive dashboards.
• Cloud: AWS (S3, EMR), GCP for ML workloads.
• Other: Git for version control, Jupyter for experimentation.

Skills and Requirements

Technical Skills

Mastery of SQL is non-negotiable—expect complex joins across billions of rows. Proficiency in Python for scripting and modeling, plus experience with dbt for modular pipelines. Familiarity with cloud data warehouses like Snowflake and orchestration tools like Airflow sets you apart.

Bonus points for causal inference libraries (DoWhy) and streaming data (Kafka). Domain knowledge in media analytics, like cohort analysis or recommendation systems, aligns perfectly with Philo's stack.

Soft Skills

Strong communication shines when translating technical findings into product stories—think presenting churn drivers to non-technical stakeholders. Teamwork thrives in Philo's collaborative environment, where you'll pair-program on tough queries. Problem-solving under ambiguity is key, as you'll often tackle ill-defined business questions with data.

Experience Expectations

Senior-level means 5+ years in analytics engineering, with proven impact like launching production pipelines. A portfolio of GitHub repos or personal projects (e.g., public dashboards on viewer trends) trumps GPA—aim for demonstrated SQL optimization or A/B wins. No PhD needed; bachelor's in CS, stats, or related suffices if backed by hands-on work.

Salary and Benefits

For a Sr. Analytics Engineer in New York (remote/hybrid), expect $160,000-$220,000 base, plus 15-20% bonus and equity vesting over four years. Levels.fyi data pegs total comp at $250K+ for similar roles at streaming peers.

Perks include full health coverage, 401k match, unlimited PTO, and $2,000 annual learning stipend for conferences like Strata. Hybrid flexibility means 2-3 days in NYC offices with stipends for home setups. High full-time conversion for strong performers, often with promotion tracks to lead roles.

Philo Hiring Process

Step-by-Step Hiring Stages

1. Application: Submit resume, LinkedIn, and cover letter via Lever ATS, highlighting data projects.
2. Screening: 30-min recruiter call assessing experience fit and salary expectations.
3. Assignment: Take-home task building a dbt model from sample streaming data (4-6 hours).
4. Interviews: 4-5 rounds: technical deep-dive, SQL live-coding, system design, behavioral with team.
5. Offer: Negotiation call with comp details; reference checks follow.

Application Timeline

Apply now for upcoming season starts in Q3-Q4 2026—postings drop 2-3 months prior. Process spans 4-6 weeks; aim to submit by June for summer/fall slots. Follow up politely after two weeks if no response.

Screening Methods

Lever ATS scans for keywords like "Snowflake," "dbt," "Python analytics," and "ETL." Tailor your resume with quantifiable impacts (e.g., "Optimized queries reducing costs 40%"). No portfolio mandatory, but linking GitHub boosts signals.

Interview Preparation

Example Interview Questions

• "Design a pipeline to track user churn in a streaming app—handle scale and late-arriving data."
• "Write SQL to find top channels by watch time per cohort, optimizing for 10B rows."
• "Explain how you'd A/B test a new recommendation algorithm, including metrics and pitfalls."
• "Walk us through debugging a dashboard showing incorrect retention rates."

How to Answer

Use STAR method: Situation, Task, Action, Result—tie to real projects. For technicals, think aloud: clarify assumptions, outline steps, code iteratively. Practice on Pramp or LeetCode for SQL; mock system design with Exponent videos tailored to data roles.

What Recruiters Evaluate

They prioritize production-ready thinking: scalability, edge cases, data quality. Cultural add—do you collaborate or go lone wolf? Impact stories over theory; quantify wins like "Pipeline cut latency 70%."

How to Get Selected

Practical Tips

• Customize cover letter with Philo-specifics, like referencing their DVR churn reductions.
• Build a quick demo dashboard on public streaming data using Looker Studio.
• Network via LinkedIn—message Philo engineers about their Strata talks.
• Practice live SQL on StrataScratch with media datasets.
• Prepare questions: "How does data team influence product prioritization?"

Common Mistakes to Avoid

• Generic resumes ignoring Philo's streaming focus—always localize.
• Rushing take-homes; incomplete tests kill 50% of candidates.
• Over-focusing theory sans examples; interviewers want battle-tested stories.
• Ignoring behavioral rounds—prep Philo values like "user obsession."

How to Stand Out

Share a tailored portfolio: GitHub with annotated streaming analytics repo. Attend NYC tech meetups; reference mutual connections. Post-interview, send thank-yous recapping a unique insight. Contribute to open-source dbt projects Philo follows.

Final Thoughts

Landing Sr. Analytics Engineer at Philo catapults your career into high-impact data work at a streaming leader. With the right prep, your blend of technical chops and business savvy will shine. Polish that application today—your future at Philo starts now.

Frequently Asked Questions

Q: What is the salary for Sr. Analytics Engineer at Philo?

A: Base ranges $160K-$220K, total comp $250K+ with bonus and equity, per market data for NYC remote roles.

Q: How competitive is it to get hired at Philo?

A: Highly competitive—expect 100+ apps per opening, but strong data portfolios cut through to 20% interview rate.

Q: What skills are most important for this role?

A: Advanced SQL, Python ETL, dbt/Snowflake, plus A/B testing and dashboarding in Looker.