Data Engineer II, Finance

Instacart
Canandaigua, NY, United States
16 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
8 years minimum
Compensation
$220,000.0 - $232,000.0
Working hours
Regular working hours
Job source

Tech stack

Airflow BigQuery Computer Engineering Information Engineering Data Infrastructure Data Integration Extract Transform Load (ETL) Data Systems Python (Programming Language) Software Engineering SQL Databases Snowflake
+8 more
Data Build Tool (dbt) Apache Spark Backend Data Strategy Data Lakes Information Technology Data Pipelines Amazon Redshift

Job description

Our backend systems power the clients used by millions of customers every year to buy their groceries online. These systems must also support tight integration with the largest retailers in the US and Canada. Engineering at Instacart provides the opportunity to work on challenging scaling problems while also designing the features that will define our industry. You will learn how to build in an open collaborative environment serving millions of requests daily.

Finance data engineering is part of the Data Infrastructure team, working closely with accounting, billing & revenue teams to support the monthly/quarterly book close, retailer invoicing and internal/external financial reporting. The team plays a critical role in defining how financial data is modeled and standardized for uniform, reliable, timely and accurate reporting. This is a high impact, high visibility role owning critical data integration pipelines and models across all of Instacart’s products.

The team is still small and many of our bigger initiatives are at an early stage. We expect you to work closely with stakeholders and shape these systems from design, technical decisions, project management to execution. Your input will be critical for driving the Finance Data Strategy and building the platform that Instacart’s financial data infrastructure will be built upon.

About the Job

  • You will work closely with finance, accounting, billing, and revenue teams to understand their main pain points and translate them into self-serve, reliable, and scalable data solutions.
  • You are expected to mentor other team members and be a champion of engineering excellence across the organization.
  • You will be part of a small team with a large amount of ownership and autonomy, managing initiatives directly from design through execution.
  • You will have the freedom to suggest and drive organization-wide initiatives that shape the financial data vision and roadmap.
  • You will own critical data integration pipelines and models, ensuring uniform, reliable, timely, and accurate financial reporting.

Requirements

  • 8+ years of working experience in a Data/Software Engineering role, with a focus on building data pipelines (specialized in financial data).
  • Strong knowledge of cloud based warehouses like Snowflake, Redshift, BigQuery.
  • Strong knowledge of common data infra technologies (Python, Airflow, Spark, Iceberg, Delta Lake) in a production environment.
  • Expert in data modeling with experience in modeling complex financial data with scalability and usability in mind.
  • Expert with SQL and dbt (Data Build Tool).
  • Experience building high quality and complex ETL/ELT pipelines including pipelines for accounting/billing purposes.
  • Experience with data immutability, auditability, slowly changing dimensions or similar concepts.
  • Adept at fluently communicating with many cross-functional stakeholders to drive requirements and design shared datasets.
  • An ability to balance a sense of urgency with shipping high quality and pragmatic solutions.
  • Experience working with a large codebase on a cross functional team., * Bachelor’s degree in Computer Science, computer engineering, electrical engineering or equivalent work experience.
  • Experience with Snowflake, dbt (Data Build Tool) and Airflow.
  • Experience with SOX controlled data systems.

LI-Remote

Benefits & conditions

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.

About the company

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.

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Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

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Empowering domain teams with an open data platform

Sandhya Menon Sandhya Menon Ā· World Congress 2026 Europe

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Career evolution in data engineering and AI platforms

Maria Apazoglou Ā· Coffee With Developers

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Structuring and scaling the backend engineering team

Stefan Lingler Stefan Lingler +1 Ā· Coffee With Developers

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Leveraging BigQuery ML for scalable SQL-based segmentation experiments

Julian Joseph Ā· LIVE

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Audience questions on AI agents and pipeline vectorization

Joy Joy Ā· World Congress 2024

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Choosing TypeScript for complex backend applications

Maximilian Otto Maximilian Otto Ā· World Congress 2024

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