トレンド企業

Instacart
Instacart

Groceries delivered in as fast as 1 hour.

Senior Analytics Engineer, Marketing

職種データエンジニアリング
経験シニア級
勤務地United States - Remote
勤務リモート
雇用正社員
掲載1ヶ月前
応募する

We're transforming the grocery industry

At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers.

Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.

Instacart is a Flex First team

There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work.

Overview

The Marketing Enablement & Technology (MET) team sits natively within Instacart's Marketing organization owning the data foundations that power Paid Marketing, SEO, and Retailer Marketing attribution. These datasets directly inform how we allocate hundreds of millions of dollars in marketing spend and how we measure growth. We're hiring a Senior Analytics Engineer to own and evolve the marketing analytics data foundation. In this role, you'll design high-quality, business-aware data models that Data Scientists and Analysts trust, while also providing technical leadership across marketing data modeling—setting standards, guiding execution, and raising the bar for how data is built, tested, documented, and delivered.

About the Job

  • Analytics Data Modeling: Design, build, and maintain high-quality dimensional and semantic data models using dbt that support marketing analytics across Paid Marketing, SEO, Retailer Marketing, and attribution.

  • Cross-functional Partnership: Work closely with Data Scientists, Analysts, and Marketing stakeholders to understand analytical needs, translate business questions into data requirements, and deliver trusted, decision-ready data assets.

  • Metrics & Definitions Ownership: Lead efforts in metric definition, business logic standardization, testing, and documentation to ensure consistent, trusted reporting across marketing.

  • Technical Leadership: Set standards for analytics engineering best practices—including code review, testing frameworks, and modeling patterns—to ensure scalability, reliability, and maintainability across the marketing data ecosystem.

  • Model Evolution & Optimization: Continuously improve existing data models to reduce complexity, improve query performance, and increase analyst self-service capabilities.

  • Scalable Analytics Infrastructure: Develop scalable analytics engineering patterns, including dimensional models, semantic layers, testing frameworks, and monitoring approaches, to support evolving marketing measurement needs.

  • AI & ML Enablement: Partner with Data Scientists & Analysts to build and maintain curated datasets that provide context for ML & AI-driven marketing applications.

About You

Minimum Qualifications

  • 5+ years of experience in Analytics Engineering or a closely related role, with ownership of production-grade analytical data models.

  • Expert-level SQL skills and deep experience designing dimensional models (star schemas, fact/dimension tables, SCDs).

  • Strong proficiency with dbt, including project structure, testing, documentation, and macros.

  • Experience with Snowflake or similar cloud data warehouses.

  • Solid understanding of marketing data and metrics, including paid media performance, attribution concepts, and channel-level measurement.

  • Demonstrated ability to set standards, guide execution, and mentor others on analytics engineering best practices.

  • Excellent judgment and product thinking—you know how to balance speed, correctness, and long-term maintainability.

Preferred Qualifications

  • Experience building or contributing to a metrics/semantic layer.

  • Familiarity with BI tools (Looker, Tableau, Hex, etc.) and optimizing models for analyst consumption.

  • Experience working directly with Data Scientists on experimentation, attribution, or incrementality measurement.

  • Familiarity with marketing platforms (e.g., Google Ads, Meta, Google Analytics, SEO tooling).

  • Python experience for automation or advanced transformations.

  • Experience introducing analytics engineering best practices in an organization that didn't previously have them.

Instacart provides highly market-competitive compensation and benefits in each location where our employees work. This role is remote and the base pay range for a successful candidate is dependent on their permanent work location. Please review our Flex First remote work policy here.

Offers may vary based on many factors, such as candidate experience and skills required for the role. Additionally, this role is eligible for a new hire equity grant as well as annual refresh grants. Please read more about our benefits offerings here.

For US based candidates, the base pay ranges for a successful candidate are listed below.

CA, NY, CT, NJ**$191,000—$201,500 USDWA$183,000—$193,000 USDOR, DE, ME, MA, MD, NH, RI, VT, DC, PA, VA, CO, TX, IL, HI$175,000—$184,500 USDAll other states$159,000—$168,000 USD**

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Instacartについて

Instacart

Instacart

Public

Maplebear Inc., doing business as Instacart, is an American retail media and delivery company based in San Francisco that operates a grocery delivery and pick-up service in the United States and Canada accessible via a website and mobile app.

1,001-5,000

従業員数

San Francisco that operates a grocery delivery

本社所在地

$39B

企業価値

レビュー

23件のレビュー

3.5

23件のレビュー

ワークライフバランス

4.2

報酬

3.8

企業文化

3.5

キャリア

2.8

経営陣

2.5

65%

知人への推奨率

良い点

Great flexibility and scheduling

Good work-life balance

Decent pay and compensation

改善点

Management issues and unresponsiveness

Job security concerns and layoffs

Inconsistent hours

給与レンジ

1,788件のデータ

Mid/L4

Senior/L5

Staff/L6

Mid/L4 · Data Scientist L4

0件のレポート

$248,100

年収総額

基本給

-

ストック

-

ボーナス

-

$210,885

$285,315

面接レビュー

レビュー1件

難易度

3.0

/ 5

期間

21-35週間

面接プロセス

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

よくある質問

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Past Experience