We are looking for a Senior Data Engineer to build and evolve the data platform powering our integral workforce management ecosystem. You will design, implement, and maintain scalable data pipelines that consolidate data from multiple operational systems, transform it into trusted analytical datasets, and make it available for reporting, product analytics, and business intelligence.

You should be comfortable working with modern cloud-native data architectures on AWS, building reliable ETL/ELT pipelines, and designing data models optimized for analytical workloads. This role requires a strong engineering mindset, balancing performance, scalability, data quality, and operational excellence while collaborating closely with software engineers, product teams, analysts, and data scientists.

What You Will Own

-
- Design, build, and maintain scalable batch and streaming data pipelines using AWS-native services and distributed processing frameworks
- Develop ETL/ELT workflows to ingest, consolidate, sanitize, enrich, and transform data from multiple internal and external systems




- Build and optimize AWS Data Lake solutions using Amazon S3, AWS Glue, Amazon Redshift, and Amazon Kinesis Firehose
- Design and implement distributed data processing jobs using Apache Spark, AWS Glue, Databricks, or equivalent technologies
- Develop orchestration workflows using Apache Airflow (MWAA), AWS Step Functions, or similar workflow orchestration platforms
- Design analytical data models including star schemas, snowflake schemas, dimensional models, and optimized reporting datasets
- Optimize Redshift performance through distribution strategies, sort keys, partitioning, workload tuning, and query optimization
- Build resilient pipelines supporting retries, idempotency, checkpointing, incremental processing, and partial failure recovery
- Implement automated data quality validation, schema evolution, lineage tracking, and governance controls
- Develop infrastructure and deployment automatio

📌 Senior Data Engineer (México)
🏢 Globalli
📍 México