# Lead Data Engineer

**Company:** [SimplePractice](https://hotfix.jobs/companies/simplepractice)
**Location:** Mexico City, Mexico
**Role:** Data Engineering
**Experience:** 7+ years
**Skills:** SQL, Python, Snowflake, dbt, AWS, Amazon S3, Amazon Rds, Amazon Redshift, Apache Airflow, Apache Kafka, Terraform, Docker, Kubernetes, Looker, Tableau
**Posted:** 2026-07-16

> Leads the architecture and delivery of scalable data platforms, pipelines, warehouses, and semantic layers supporting analytics, reporting, product experiences, and AI evaluation. Requires 7+ years in data or analytics engineering and strong expertise in SQL, data modeling, Snowflake, dbt, orchestration, and AWS.

## Job Description

## Responsibilities
- Partner with Product, Analytics, and Engineering to build scalable systems that unlock data from backend databases, event streams, and marketing platforms.
- Lead technical vision and architecture across short-term and long-term horizons.
- Create company-wide alignment through standardized metrics.
- Support financial reporting, product analytics, and operational metrics.
- Enable customer-facing dashboards, self-serve analytics, and next-best-action capabilities.
- Manage the complete data stack from ingestion through data consumption.
- Build tools that increase transparency in company-wide business outcomes.
- Work with DevOps to deploy and maintain data solutions using cloud data technologies, preferably AWS.
- Define data quality and security frameworks and promote data engineering best practices.

## Requirements
### Education and Experience
- Bachelor's or master's degree in Engineering, Computer Science, Mathematics, or a related field.
- 7+ years of experience in data or analytics engineering.
- Strong problem-solving and communication skills.
- Comfortable working in fast-paced, cross-functional environments.

### Data Engineering and Pipelines
- Experience with enterprise architecture, enterprise data architecture, data modeling, and dimensional modeling.
- Expert knowledge of SQL and relational, dimensional, and semantic data modeling.
- Experience designing, implementing, and maintaining data warehouses, including Snowflake.
- Hands-on experience with dbt for modular, testable transformations.
- Experience with orchestration and ingestion tools such as Airflow, Prefect, Airbyte, Fivetran, and Kafka.
- Familiarity with ELT, schema-on-read, DAGs, and performance optimization.

### Cloud and Infrastructure
- Experience with AWS, including S3, RDS, and Redshift.
- Familiarity with Terraform, Docker, and containerized workflows.
- Experience handling structured, semi-structured JSON, and columnar formats such as Parquet and ORC.

### Analytics and Enablement
- Experience building and supporting semantic layers for self-serve analytics.
- Proficiency with BI tools such as Looker, Tableau, or Sisense.
- Experience standardizing metrics and enabling trusted, consistent access to data.

### Programming and Scripting
- Proficiency in Python and Unix/Linux scripting.
- Experience working with APIs, including curl.

## Nice-to-Haves
- AWS DevOps experience with Terraform, Kubernetes, and Docker.
- Project and change management experience, particularly in Agile Scrum or Kanban environments.
- Real-time ETL experience with Kafka streaming or AWS Kinesis.

## Compensation and Benefits
- Private medical, dental, and vision coverage.
- Supplemental health and wellness benefits.
- Work-from-home stipend.
- Flexible Time Off, wellbeing days, Summer Fridays, company holidays, and paid holidays.
- 15-day Christmas bonus (aguinaldo).
- Monthly meal or grocery voucher via Si Vale card.
- Catered lunch.
- Relocation bonus for candidates joining from a different city.
- Annual bonus.
- Tuition reimbursement.
- Savings fund.
- Employee Resource Groups (ERGs).

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