Senior Data Engineer
Senior Data Engineer responsible for architecting and operating scalable data pipelines, warehouses, and analytics infrastructure. The role requires 7+ years of data or analytics engineering experience, strong SQL and modeling expertise, and proficiency with cloud, orchestration, and BI technologies.
About the job
Responsibilities
- Build scalable data systems and pipelines from backend databases, event streams, and marketing platforms.
- Lead data architecture and technical vision across short- and long-term horizons.
- Standardize company-wide metrics and support financial reporting, product analytics, and operational metrics.
- Enable customer-facing dashboards, self-serve analytics, and next-best-action product use cases.
- Manage the complete data stack from ingestion through data consumption.
- Build tools that improve transparency into business outcomes.
- Deploy and maintain cloud-based data solutions with DevOps teams, preferably using AWS.
- Define data quality and security frameworks and promote data engineering best practices.
Requirements
- 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 in fast-paced, cross-functional environments.
- Experience with enterprise and dimensional data architecture, data modeling, and data warehouse design.
- Expert SQL skills and experience with relational, dimensional, and semantic models.
- Experience implementing and maintaining Snowflake data warehouses.
- 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.
- Experience with AWS services including S3, RDS, and Redshift.
- Experience handling structured, semi-structured JSON, and columnar formats such as Parquet and ORC.
- Experience building semantic layers for self-service analytics.
- Proficiency with BI tools such as Looker, Tableau, or Sisense.
- Proficiency in Python and Unix/Linux scripting.
- Experience working with APIs and tools such as curl.
Nice-to-haves
- Terraform, Kubernetes, and Docker.
- Agile project and change management experience, including Scrum or Kanban.
- Real-time ETL using Kafka streaming or AWS Kinesis.
Compensation and Benefits
- Annual base compensation: $977,440–$1,221,820 MXN.
- Medical, dental, and vision coverage.
- Health and wellness benefits.
- Work-from-home stipend.
- Flexible time off, wellbeing days, company holidays, and recharge periods.
- Christmas bonus, monthly meal or grocery voucher, and catered lunch.
- Relocation bonus, annual bonus, tuition reimbursement, and savings fund.
Skills
SQL, Data Modeling, Snowflake, dbt, Apache Airflow, Prefect, Airbyte, Fivetran, Apache Kafka, AWS, Terraform, Docker, Python, Kubernetes, Looker
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