Senior Data Platform Engineer - Cloud, AI & Governance

HCLTech; México; Presencial; MXN 900.000 - 1.300.000; Jornada completa

Descripción de la vacante

HCLTech is seeking an experienced Lead Data Engineer to design, build and evolve enterprise-grade data platforms and pipelines. You will lead the migration of legacy data assets to cloud-based architectures, implement scalable ETL/ELT frameworks, and drive data quality, lineage, governance, observability, and monitoring across the data ecosystem.

The role requires deep expertise in Databricks, Spark, Delta Lake, SQL, Hadoop and Python, with experience on Azure, AWS, or GCP.

Formación

• Design and implement large-scale data engineering solutions.
• Experience with cloud platforms (Azure/AWS/GCP).
• ETL/ELT pipelines, streaming architectures, and data integration frameworks.
• Data modeling for analytical and operational workloads.
• Data quality, lineage, metadata management, and governance.

Responsabilidades

• Lead design, development, and evolution of enterprise-grade data platforms and pipelines.
• Architect scalable ETL/ELT frameworks using Databricks, Spark, Delta Lake, and cloud-native tech.
• Establish data quality, lineage, governance, observability, and monitoring.
• Drive migration of legacy data assets to cloud Data Lakehouse architectures.
• Collaborate with Risk, Product, Architecture, and Engineering to translate requirements into scalable solutions.
• Lead technical reviews and set engineering standards and practices.
• Mentor engineers to raise technical capability and ownership across teams.
• Shape roadmap planning, tech evaluation, and delivery priorities across data platforms.

Conocimientos

Distributed data processing

Leadership

Communication

Data governance

Problem solving

Educación

Bachelor's degree in Computer Science or related STEM

Herramientas

Databricks

Apache Spark

Delta Lake

SQL

Hadoop

Python

Airflow

Descripción del empleo

HCLTech is seeking an experienced Lead Data Engineer to design, build and evolve enterprise-grade data platforms and pipelines. You will lead the migration of legacy data assets to cloud-based architectures, implement scalable ETL/ELT frameworks, and drive data quality, lineage, governance, observability, and monitoring across the data ecosystem.

The role requires deep expertise in Databricks, Spark, Delta Lake, SQL, Hadoop and Python, with experience on Azure, AWS, or GCP.