Senior Data Platform Engineer – AWS, ETL & Analytics

Globalli; Colombia; Presencial; COP 120.000.000 - 180.000.000; Jornada completa

Descripción de la vacante

Globalli in Colombia is seeking a Senior Data Engineer to design, build, and evolve a scalable data platform powering our global workforce ecosystem. You will craft data pipelines, implement ETL/ELT workflows, and enable reporting, analytics, and BI across multiple teams.

You will work with AWS-native data services, Spark, Databricks, Airflow, and CI/CD practices, shaping data models and governance while ensuring reliability, performance, and data quality.

Formación

• 5+ years of professional experience building production data pipelines and cloud-based data platforms.
• Strong experience with AWS data services including Amazon Redshift, AWS Glue, Amazon S3, and Amazon Kinesis Firehose.
• Strong Python programming skills for ETL development, automation, event processing, and scripting.
• Advanced SQL expertise including query optimization, window functions, analytical queries, versioned migrations, rollback strategies, and warehouse tuning.
• Experience designing scalable ETL/ELT pipelines for both batch and streaming workloads.
• Experience with distributed compute and storage using Apache Spark, AWS Glue, Databricks, or similar distributed processing frameworks.
• Strong understanding of data warehousing concepts including dimensional modeling, star schemas, snowflake schemas, partitioning strategies, and analytical data structures.
• Experience designing end-to-end data architectures including ingestion, transformation, orchestration, and consumption layers.
• Experience implementing workflow orchestration using Apache Airflow (MWAA), AWS Step Functions, or equivalent orchestration tools.
• Understanding of data governance, metadata management, security best practices, IAM, encryption, and regulatory compliance considerations.
• Experience with Git-based collaborative development workflows, CI/CD pipelines, Infrastructure as Code, deployment approvals, versioned migrations, and safe rollback strategies.
• Experience monitoring and maintaining production data infrastructure, ensuring high availability, observability, data quality, and operational reliability.
• Strong communication skills with the ability to explain technical concepts to business stakeholders and collaborate effectively across engineering, analytics, and product teams

Responsabilidades

• 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 automation using Infrastructure as Code and CI/CD pipelines
• Monitor, troubleshoot, and continuously improve the reliability, scalability, and performance of the data platform
• Collaborate with analysts, software engineers, data scientists, and product managers to translate business requirements into scalable data solutions
• Participate in architecture discussions and contribute technical documentation, standards, and best practices

Conocimientos

Python

SQL

ETL/ELT development

Apache Spark

Airflow

AWS data services

Herramientas

Amazon Redshift

AWS Glue

Amazon S3

Amazon Kinesis Firehose

Databricks

Apache Spark

Airflow MWAA

Git

Terraform

CloudFormation

Descripción del empleo

Globalli in Colombia is seeking a Senior Data Engineer to design, build, and evolve a scalable data platform powering our global workforce ecosystem. You will craft data pipelines, implement ETL/ELT workflows, and enable reporting, analytics, and BI across multiple teams.

You will work with AWS-native data services, Spark, Databricks, Airflow, and CI/CD practices, shaping data models and governance while ensuring reliability, performance, and data quality.