Lead Data Engineer

SimplePractice

Lead Data Engineer responsible for evolving data stack and building infrastructure for health tech company. Collaborate across teams to support analytics, reporting, and insights for clinicians.

Posted 6/23/2026full-timeMexico City • 🇲🇽 MexicoSeniorWebsite

Tech Stack

Tools & technologies

AirflowAmazon RedshiftAWSCloudDockerKafkaLinuxPythonSQLTableauTerraformUnix

About the role

Key responsibilities & impact

Partner with Product, Analytics and Engineering to build scalable systems that help unlock the value of data from a wide range of sources such as backend databases, event streams, and marketing platforms
Lead technical vision and architecture with holistic point of view on both short-term and long-term horizons
Work with analytics to create company wide alignment through standardized metrics across the company
Work with Product and Engineering teams to support internal use cases such as financial reporting, product analytics and operational metrics
Enable external use cases like customer-facing dashboard, self-serve analytics, and next best action in product
Manage the complete data stack from ingestion through data consumption
Build tools to increase transparency in reporting company wide business outcomes
Work with DevOps to deploy and maintain data solutions leveraging cloud data technologies, preferably in AWS
Help define data quality and data security framework to measure and monitor data quality across the enterprise. Define and promote data engineering best practice

Requirements

What you’ll need

BS/MS in Engineering, Computer Science, Mathematics, or related field
7+ years in Data or Analytics Engineering
Strong problem-solving and communication skills; comfortable in fast-paced, cross-functional environments
Enterprise architecture and enterprise data architecture (data modeling and enterprise dimensional modeling)
Expert in SQL and data modeling (relational, dimensional, semantic)
Proven experience in data warehouse design, implementation, and maintenance (Snowflake)
Hands-on with DBT for modular, testable transformations
Experience with orchestration and ingestion tools: Airflow, Prefect, Airbyte, Fivetran, Kafka
Familiar with ELT, schema-on-read, DAGs, and performance optimization
Experience with AWS (S3, RDS, Redshift, etc.)
Familiar with Terraform, Docker, and containerized workflows (bonus)
Skilled in handling structured, semi-structured (e.g., JSON), and columnar formats (e.g., Parquet, ORC)
Experience building and supporting semantic layers for self-serve analytics
Proficient with BI tools like Looker, Tableau, or Sisense
Comfortable standardizing metrics and enabling trusted, consistent access to data
Proficient in Python and Unix/Linux scripting
Comfortable working with APIs (e.g., using curl)

Benefits

Comp & perks

Privatized Medical, Dental & Vision Coverage
Work From Home stipend
Flexible Time Off (FTO), wellbeing days, paid holidays, and Summer Fridays
Monthly Meal Reimbursement
Holiday Bonus, 15-day Aguinaldo
Hybrid Work Schedule & Catered Lunch
A relocation bonus for candidates joining us from a different city
Employee Resource Groups (ERGs)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

SQLdata modelingdata warehouse designSnowflakeDBTAirflowPrefectFivetranKafkaPython

Soft Skills

problem-solvingcommunicationcross-functional collaborationleadershiporganizational skills