Lead Data Engineer (AWS)

Office in Mexico: Mexico City

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We are looking for a forward-thinking Lead Data Engineer to help shape and advance the Client’s data infrastructure and vision.

In this position, you will tackle key challenges like unifying multiple data sources and steering cloud migration efforts to phase out legacy business intelligence systems. Your contributions will support the Client’s move toward a Data Mesh approach, broaden access to data products, and strengthen analytics across BI, ML, AI, Deep Learning, and IoT domains.

Responsibilities

Design and deliver data warehouse architectures and establish reliable ETL/ELT workflows to maintain data quality and accessibility
Build and refine data pipelines leveraging AWS technologies such as Glue, Redshift, Athena, DynamoDB, and Amazon RDS
Develop and update automation scripts for pipeline operations, including Glue scripts for creating parameterized parquet files
Oversee the transition of data assets and workflows to the cloud, enabling the retirement of multi-platform BI solutions
Facilitate smooth data integration across a variety of platforms, sources, and formats to drive the adoption of a Data Mesh model
Work closely with engineers, analysts, and administrators to capture business requirements and deliver tailored data solutions
Collaborate with business stakeholders to clarify data needs, estimate project scope, and construct pipelines for Data Lake ingestion
Contribute to the creation of Redshift data models that power BI visualizations in Tableau Cloud or Server
Strengthen the BI environment while enabling the development of advanced ML, AI, and Deep Learning solutions
Prepare and maintain documentation for database structures, ETL/ELT processes, security models, and architectural diagrams
Uphold rigorous data governance practices to guarantee data reliability, protection, and accessibility
Construct Glue Data Pipelines to bring in data from APIs, transform it, and load it into cloud storage
Write Glue scripts to generate parameterized parquet files in JSON format and automate their storage in the cloud
Design and deploy Redshift data models for metrics to be visualized in Tableau
Support business teams in defining data requirements, estimating workloads, and delivering pipeline solutions for Data Lake integration

Requirements

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
At least 5 years of hands-on experience in data engineering
Minimum one year of experience leading and managing technical teams
Demonstrated expertise with AWS data services, including S3, Glue, Redshift, Lambda, DynamoDB, Athena, and RDS
In-depth knowledge of ETL/ELT processes, data pipeline design, and contemporary data warehousing principles
Proficiency in programming languages such as Python, SQL, or Scala
Experience building, deploying, and tuning data models in Redshift or comparable platforms
Strong analytical and troubleshooting abilities with a keen eye for detail
Excellent interpersonal skills and a proven ability to work effectively with both technical and business teams
Advanced English proficiency, both written and spoken, at B2+ level or above

Nice to have

Experience with data visualization platforms, particularly Tableau Server or Tableau Cloud
Background in implementing Data Mesh architectures
Understanding of machine learning, deep learning, AI, and IoT technologies
Familiarity with big data tools like Apache Spark and Hadoop
Knowledge of JSON schema design and managing cloud storage
Hands-on experience with AWS Lambda and Amazon EC2