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Data Analytics Lead Remote information
See salary details
$60.5K - $70.9K
4% of jobs
$70.9K - $81.3K
6% of jobs
$81.3K - $91.7K
7% of jobs
$96.6K is the 25th percentile. Wages below this are outliers.
$91.7K - $102.1K
16% of jobs
$102.1K - $112.5K
9% of jobs
The median wage is $120.6K / yr.
$112.5K - $123K
9% of jobs
$123K - $133.4K
13% of jobs
$133.4K - $143.8K
8% of jobs
$147.2K is the 75th percentile. Wages above this are outliers.
$143.8K - $154.2K
6% of jobs
$154.2K - $164.6K
13% of jobs
$164.6K - $175K
8% of jobs
$60.5K
$123.8K
$175K
How much do data analytics lead remote jobs pay per year?
What does a Data Analytics Lead do when working remotely?
What is the difference between Data Analytics Lead Remote vs Data Analyst Remote?
| Aspect | Data Analytics Lead Remote | Data Analyst Remote |
|---|---|---|
| Required Credentials | Bachelor's/Master's in Data Science, Analytics, or related field; experience in leadership roles | Bachelor's in Data Science, Statistics, or related field; entry to mid-level experience |
| Work Environment | Leading analytics projects, managing teams, strategic planning | Data collection, analysis, reporting, supporting decision-making |
| Employer & Industry Usage | Tech companies, finance, healthcare, consulting firms | Similar industries, often within larger teams or departments |
The main difference between Data Analytics Lead Remote and Data Analyst Remote lies in their responsibilities and seniority. The Lead typically manages analytics teams and oversees strategic projects, requiring more experience and leadership skills. In contrast, Data Analysts focus on data collection, analysis, and reporting tasks. Both roles are vital in data-driven organizations, but the Lead holds a broader scope and higher level of responsibility.
What are the key skills and qualifications needed to thrive as a Data Analytics Lead in a remote setting, and why are they important?
How does a Data Analytics Lead typically collaborate with cross-functional teams in a remote setting?

Full-time
Posted 14 days ago
Job description
You've never worked for a company quite like Pearmill. We're a bunch of eclectic folks paving our own path in the world of technology, marketing, and advertising.
We're a diverse group of designers, engineers, and marketers from across the world, working together to help grow challenger brands and fast-growing startups through art and technology.
Pearmill is a performance marketing agency that outperforms expectations, using data-driven insights and relentless innovation for exponential growth.
About the role
We're looking for an Analytics Lead to own the full measurement stack - from the pixels firing on a client's checkout page to the incrementality test that tells us whether that Meta campaign is actually moving the needle. This is a player-coach role: you'll set the measurement philosophy and learning agenda for the agency, manage a junior tracking specialist who handles hands-on QA and implementation, and work directly with client teams to translate data into decisions.
This role sits at the intersection of analytics engineering, measurement science, and performance strategy. You won't just build dashboards - you'll design the tests that prove whether our work is working.
What you'll own
Tracking & data infrastructure
- Own the end-to-end tracking architecture across all client accounts: Google Tag Manager, GA4, CDPs (Segment, RudderStack, Teleaum, etc.), Meta Pixel + CAPI, Google Ads Enhanced Conversions, TikTok Events API, and any other ad network data pipelines - and be well versed enough in these systems to support clients hands-on with implementation
- Define tagging standards, naming conventions, and data layer specifications for new client onboarding
- Review and sign off on all pixel/tag implementations done by the junior tracking specialist before anything goes live
- Lead tracking QA processes: diagnose misfires, validate conversion events, and ensure data integrity across environments (dev, staging, production)
- Own server-side tracking setups and consent-mode configurations as privacy requirements evolve
- Build measurement plans for every client: define the KPIs that actually matter, the attribution approach best suited to their funnel, and the testing roadmap for the next 6-12 months
- Design and run incrementality tests - geo-based holdouts, PSA holdout tests, conversion lift studies - and translate results into media budget recommendations
- Interpret and pressure-test platform-reported metrics (Meta Ads Manager, Google Ads, etc.); challenge results that don't hold up to scrutiny
- Lead or collaborate on Marketing Mix Modeling (MMM) engagements - either scoping vendor-run models or building lightweight versions in-house
- Own the cross-channel attribution model: evaluate last-click vs. data-driven vs. time-decay approaches per client context and document your rationale
- Build and maintain executive-level dashboards (Looker Studio, Looker, Power BI, or equivalent) that go beyond vanity metrics to show incremental business impact
- Establish a regular reporting cadence: weekly performance pulse, monthly deep-dives, and quarterly measurement reviews with clients
- Write clear, opinionated insight narratives - not just charts - that connect data to the decisions clients need to make
- Manage one junior Analytics/Tracking Specialist: set their priorities, review their work, give them a clear growth path
- Build the analytics practice playbook: onboarding templates, tracking specs, measurement plan frameworks, experiment design guides
- Stay current on the ad platform measurement landscape - platform pixel changes, consent/privacy shifts, new incrementality products from Meta, Google, TikTok - and update internal practices accordingly
- 4-7 years of experience in marketing analytics, measurement, or marketing science at a performance agency or fast-moving in-house growth team
- Hands-on GTM expertise: you've built complex container setups yourself, not just documented them for a developer
- Real incrementality testing experience - you've designed a geo holdout or conversion lift test, run it, and presented the results to a skeptical client
- Solid understanding of the full ad network measurement stack: Meta CAPI, Google Enhanced Conversions, GA4 event model, server-side tagging, and how privacy regulations affect all of it
- Proficiency in SQL - you can write your own queries to pull and validate raw data without asking a data engineer
- Ability to communicate complex findings to non-technical stakeholders without dumbing them down or losing accuracy
- Comfortable being the final word on "is our tracking trustworthy?" for a portfolio of clients simultaneously
- Python or R experience for statistical modeling or automation
- Experience building or interpreting Marketing Mix Models
- Familiarity with measurement platforms like Northbeam, Triple Whale, Measured, or Rockerbox
- Prior experience managing or mentoring a junior analyst
This is not a pure data engineer role - you won't spend all day writing pipelines. It's also not a media buyer role - you won't own campaign execution. You're the person between the two: you make sure the data is trustworthy, and then you use that data to tell us what's actually working.
Type: Full-Time • Location: Remote (North America, Western Europe)
Diversity, Equity, and Inclusion
Pearmill is a diverse company with team members hailing from all backgrounds and walks of life. We're a globally-distributed team and committed to continuing to build a company that represents the world we live in. We encourage candidates of underrepresented groups to apply.