Data Engineer Analyst

Blend; Región Centro; Sur place; MXN 450 000 - 750 000; Plein temps

Avantages offerts par ce poste

Christmas Bonus

Saving Fund

Food/grocery vouchers

Home Office allowance

Résumé du poste

Blend is seeking a Data Engineer Analyst to design, build, and optimize scalable data pipelines on AWS. You will work with Spark/PySpark to process large datasets, implement Iceberg-based data lake architectures, and leverage Glue, Athena, and Lambda for orchestration and querying.

The role emphasizes data quality, security through IAM, and collaboration with data analysts, scientists, and engineers to deliver production-ready data solutions. English is required for global teamwork.

Qualifications

• 2+ years of experience in Data Engineering or related roles.
• Hands-on experience building cloud-based data pipelines on AWS.
• Experience with Spark/PySpark for data processing.
• Familiarity with data lake architectures and Iceberg is a plus.
• Strong SQL skills for querying, validation and analysis.
• Knowledge of data modeling and large-scale processing.
• Able to communicate technical concepts to non-technical stakeholders.

Responsabilités

• Design, build, and maintain scalable data pipelines and ingestion frameworks for batch, streaming, and CDC patterns.
• Develop and optimize data processing workflows using Spark and PySpark.
• Implement and manage data lake architectures on AWS (S3, Iceberg).
• Work with Glue, Athena, and Lambda for ETL and querying tasks.
• Manage data access controls using AWS IAM and ensure security best practices.
• Collaborate with analysts, data scientists, and platform engineers to deliver production-ready solutions.
• Monitor pipelines, troubleshoot data quality, and improve reliability.
• Document data flows, architecture decisions, and engineering standards.

Connaissances

AWS services

Spark / PySpark

Data lake architecture

CDC / streaming

SQL querying

Data modeling

Cross-functional collaboration

Infrastructure as code

Airflow

dbt

Step Functions

AWS Glue

Athena

Lambda

Outils

Airflow

dbt

Step Functions

Terraform

AWS Glue

Athena

Lambda

Description du poste

Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com

We are seeking a Data Engineer Analyst to contribute to our next level of growth and expansion.

Job Description

What is this position about?

• Design, build, and maintain scalable data pipelines and ingestion frameworks supporting batch processing, streaming, and change data capture (CDC) patterns.
• Develop and optimize data processing workflows using Apache Spark and PySpark, ensuring reliable and performant transformation across large datasets.
• Implement and manage data lake architectures on AWS, leveraging S3 as the primary storage layer and Apache Iceberg for table format management, schema evolution, and time-travel capabilities.
• Work with AWS-native services including Glue for ETL orchestration, Athena for serverless querying, and Lambda for event-driven data processing.
• Manage data access controls and security configurations using AWS IAM, ensuring compliant and least-privilege access across the data platform.
• Collaborate with data analysts, data scientists, and platform engineers to understand data requirements and deliver production-ready solutions.
• Monitor pipeline health, troubleshoot data quality issues, and implement improvements to ensure data reliability and freshness.
• Contribute to the documentation of data flows, architecture decisions, and engineering standards within the team.

Qualifications

• Advanced hands-on experience with AWS services, including:
  • AWS Glue
  • Amazon S3
  • Amazon Athena
  • AWS IAM
• Apache Spark / PySpark for data processing.
• Data lake architectures, ideally with knowledge of Apache Iceberg.
• Data ingestion patterns, including batch processing, streaming, and CDC patterns
• Experience with SQL for data querying, validation, and exploratory analysis
• Solid understanding of data modeling and large-scale data processing
• Ability to work collaboratively in cross-functional teams and communicate technical concepts clearly to non-technical stakeholders.
• Experience with infrastructure-as-code or pipeline orchestration tools (e.g., Airflow, Step Functions, dbt) is a plus.
• Familiarity with AI-assisted development workflows and engineering productivity tools

What about languages?

English: Advanced (required for effective communication with global teams)

How much experience must I have?

2+ years of experience in Data Engineering or related roles, with hands-on work building and maintaining cloud-based data pipelines and lake architectures on AWS.

Additional Information

Our Perks and Benefits:

• Christmas Bonus.
• Saving Fund.
• Food/grocery vouchers.
• Home Office allowance.

Health & Insurance:

• MetLife Life Insurance with funeral coverage.
• MetLife Medical Insurance including dental discounts and vision plan.
• Dependents optional with additional cost.

Time Off & Holidays:

• Vacation days with annual increases based on tenure.
• Vacation premium.
• Official holidays by law.
• Holy week.
• Day of the Dead.
• Christmas Eve.

Work-Life Balance:

• Flexible working options to help you strike the right balance.

Learning Opportunities:

• Study plans, courses, and professional development opportunities.
• English lessons to support your professional communication.