Data Engineer (Snowflake / Systems Integration)

Getsquire; Buenos Aires; Presencial; ARS 1.200.000 - 2.400.000; Jornada completa

Descripción de la vacante

SQUIRE is seeking a Data Engineer to design and maintain data pipelines between CRM, billing, internal platforms, and a Snowflake data warehouse. You will ensure data accuracy, accessibility, and trust across the company, partnering with TechOps and Analytics on cross‑system initiatives and dashboards.

You will develop ELT/ETL processes, model data for analytics, and implement data quality checks while collaborating with non‑technical stakeholders.

Formación

• 5+ years of experience as a data engineer or in an integration/backend role.
• Strong Snowflake experience or equivalent cloud data warehouse; advanced SQL; and Python for data engineering.
• Hands-on experience integrating SaaS business systems via REST APIs, webhooks, and bulk data interfaces.
• Experience with at least one ELT/integration platform (Fivetran, Airbyte, Hightouch, Census, Workato, MuleSoft, or equivalent).
• Experience with a transformation framework (dbt strongly preferred) and workflow orchestration (Airflow, Dagster, Prefect, or similar).
• Solid understanding of data modeling (dimensional, normalized, junction objects); familiarity with reverse ETL patterns, including Polytomic.
• Practical experience with data quality, deduplication, and master data management (MDM) concepts.
• Experience with Git and CI/CD pipelines; strong problem‑solving skills and ability to debug across systems, networks, and APIs.
• Excellent communication and collaboration skills; this role works directly with non‑technical cross‑functional stakeholders.
• Bachelor's degree in Computer Science or Engineering.
• English proficiency is required; must be based in Buenos Aires with availability to work on‑site in our office in CABA two days a week (Tuesdays and Thursdays).

Responsabilidades

• Design, build, and maintain bidirectional data pipelines between operational systems (CRM, billing, internal platforms, marketing/sales/CX tools) and Snowflake.
• Build integrations that surface data from internal systems back into CRM and other downstream business tools as a reliable source of truth.
• Partner with TechOps and Analytics & Insights on cross‑system initiatives: data cleanup, schema changes, new tool rollouts, and reporting/dashboard enablement.
• Develop and maintain ELT/ETL processes with clear orchestration, scheduling, monitoring, and alerting.
• Model data in Snowflake to support analytics, reporting (Tableau, Looker), and AI/LLM use cases.
• Implement data quality checks, validation rules, and reconciliation logic to catch drift between systems before it reaches end users.
• Translate business definitions into accurate, scalable data structures.
• Audit existing automations and integrations; rip‑and‑replace where they create duplicate or bad data.
• Build and maintain CI/CD for data pipelines and SQL/transformation code; document data contracts, schemas, and lineage so other teams can self‑serve with confidence.
• Troubleshoot and resolve pipeline failures, data discrepancies, and integration issues across the stack.
• Build and maintain a data dictionary covering key fields, definitions, owners, and source systems, making it easy for any team to understand what data exists, where it lives, and what it means.

Conocimientos

Snowflake

Python

REST APIs

ELT/ETL

dbt

Airflow

Data modeling

Git & CI/CD

Communication

English

Educación

Bachelor's degree in CS or Engineering

Herramientas

BigQuery

Redshift

dbt

Airflow

Dagster

Prefect

Fivetran

Airbyte

Hightouch

MuleSoft

Descripción del empleo

WHO WE ARE

SQUIRE is the leading business management system designed for the needs of barbers, shop owners, and their communities. We believe the pursuit of artistry and autonomy should not be restricted by the complexities of running a business. With SQUIRE, we provide custom‑branded tools, resources, and guidance to help barbers of all stages and experience levels attract and retain more customers, efficiently manage their shop operations, and increase their revenue.

Founded in 2015, SQUIRE is trusted by more than 30,000 barbers across 5,000+ shops in more than a thousand cities worldwide. From streamlined booking and opening new shops to real‑time earning dashboards and building lasting customer relationships, SQUIRE supports shop owners in seamlessly bridging the gap between their personal craft and business goals. SQUIRE enables barbers everywhere to unlock their full potential both as artists and as entrepreneurs.

POSITION TITLE

Data Engineer (Snowflake / Systems Integration)

SUMMARY

The Data Engineer is responsible for building and maintaining the data pipelines, integrations, and infrastructure that move data bidirectionally across SQUIRE's business systems: CRM, billing, internal platforms, and our Snowflake data warehouse. This role ensures our data is accurate, accessible, and trustworthy across the company.

This person will partner closely with the TechOps and Analytics & Insights teams on cross‑system initiatives, dashboards, and data quality work. They will design integrations that keep operational systems and the warehouse in sync, surface internal platform data into downstream CRM and revenue tools, and enable reliable reporting and AI/automation use cases.

As part of the Operations extended team, the Data Engineer collaborates across the company. Hiring and technology policies are defined and owned by the Engineering Manager.

REPORTS TO

Direct: Engineering Manager; Dotted: Operations

RESPONSIBILITIES

• Design, build, and maintain bidirectional data pipelines between operational systems (CRM, billing, internal platforms, marketing/sales/CX tools) and Snowflake.
• Build integrations that surface data from internal systems back into CRM and other downstream business tools as a reliable source of truth.
• Partner with TechOps and Analytics & Insights on cross‑system initiatives: data cleanup, schema changes, new tool rollouts, and reporting/dashboard enablement.
• Develop and maintain ELT/ETL processes with clear orchestration, scheduling, monitoring, and alerting.
• Model data in Snowflake to support analytics, reporting (Tableau, Looker), and AI/LLM use cases.
• Implement data quality checks, validation rules, and reconciliation logic to catch drift between systems before it reaches end users.
• Translate business definitions into accurate, scalable data structures.
• Audit existing automations and integrations; rip‑and‑replace where they create duplicate or bad data.
• Build and maintain CI/CD for data pipelines and SQL/transformation code; document data contracts, schemas, and lineage so other teams can self‑serve with confidence.
• Troubleshoot and resolve pipeline failures, data discrepancies, and integration issues across the stack.
• Build and maintain a data dictionary covering key fields, definitions, owners, and source systems, making it easy for any team to understand what data exists, where it lives, and what it means.

The duties and responsibilities outlined above are not a comprehensive list, and additional tasks may be assigned based on business needs.

QUALIFICATIONS

• 5+ years of experience as a data engineer or in a closely related integration/backend role.
• Strong experience with Snowflake (warehousing, performance tuning, RBAC, Snowpipe/streams/tasks) or equivalent cloud data warehouse (BigQuery, Redshift); advanced SQL (window functions, CTEs, performance optimization); and Python for data engineering (pandas, requests, API clients, scripting).
• Hands‑on experience integrating SaaS business systems (CRM, billing, marketing/sales/CX platforms) via REST APIs, webhooks, and bulk data interfaces.
• Experience with at least one ELT/integration platform (Fivetran, Airbyte, Hightouch, Census, Workato, MuleSoft, or equivalent) and ability to evaluate when to buy vs. build.
• Experience with a transformation framework (dbt strongly preferred) and workflow orchestration (Airflow, Dagster, Prefect, or similar).
• Solid understanding of data modeling (dimensional, normalized, junction objects); familiarity with reverse ETL patterns (warehouse back to operational systems), including Polytomic.
• Practical experience with data quality, deduplication, and master data management (MDM) concepts.
• Experience with Git and CI/CD pipelines; strong problem‑solving skills and ability to debug across systems, networks, and APIs.
• Excellent communication and collaboration skills; this role works directly with non‑technical cross‑functional stakeholders.
• Bachelor's degree in Computer Science or Engineering.
• English proficiency is required; must be based in Buenos Aires with availability to work on‑site in our office in CABA two days a week (Tuesdays and Thursdays).
• Nice to have: Experience with Salesforce data model and APIs, Stripe or similar billing platforms, Gong, marketing automation, or LLM/AI platform integrations, and exposure to data governance frameworks and PII/compliance handling.

INTERVIEW ACCOMMODATIONS

SQUIRE is committed to working with and providing reasonable assistance to individuals with physical and mental disabilities. If you are an individual with a disability requiring an accommodation to apply for an open position, please email your request to [e-mail] and someone on our team will respond to your request.

EQUAL EMPLOYMENT OPPORTUNITY

SQUIRE provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

PAY TRANSPARENCY NONDISCRIMINATION PROVISION

SQUIRE will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor’s legal duty to furnish information.