Data Engineer – Semi Senior Adv

LATAM

What you’ll be doing?

As a Data Engineer at DinoCloud, you will design, build, and maintain data solutions on AWS. You will work on a variety of projects, including data lakes, data warehouses, batch and real-time data pipelines, and data preparation for multi-agent and multi-modal AI solutions.

  • Design, build, and maintain scalable data pipelines (ETL/ELT), both batch and streaming.
  • Build and operate data architectures on AWS (data lakes, data warehouses, lakehouses).
  • Identify and resolve data quality issues, performance bottlenecks, and structural inconsistencies.
  • Ensure data quality, integrity, and governance through validation, cleaning, and monitoring processes.
  • Optimize query performance, data jobs, and infrastructure costs.
  • Evaluate and propose improvements to data flows and cloud infrastructure, with a continuous improvement mindset.
  • Implement solutions using Infrastructure as Code (IaC).
  • Participate in migrations from legacy data platforms to AWS.
  • Document data architectures, pipelines, and technical decisions.
  • Collaborate closely with AI teams to prepare data for analytical and machine learning models.
  • Provide technical guidance and support to internal teams across Dino Cloud.

What would you need to succeed in this role?

  • 2+ years of experience in Data Engineering roles.
  • Strong hands-on experience with AWS data services (Glue, S3, Athena, Redshift, RDS, DynamoDB, among others).
  • Solid knowledge of SQL, including optimization, indexing, and partitioning.
  • Proven experience designing and implementing ETL/ELT data pipelines.
  • Understanding of data modeling concepts (dimensional modeling, Data Vault, etc.).
  • Familiarity with Python for data processing and automation.
  • Experience using Git and basic CI/CD practices.
  • Intermediate to Upper-Intermediate English (B2+), for technical documentation and meetings. A validation will be performed in the first step of the process.
It is a plus if you have:
  • Experience with streaming / real-time data processing (Kinesis, MSK, Kafka).
  • Knowledge of Infrastructure as Code tools (Terraform, CDK, CloudFormation).
  • Experience with Spark (PySpark, EMR, AWS Glue).
  • Familiarity with data quality, lineage, and governance tools.
  • Experience with NoSQL databases.
  • Experience with SAP (BW, HANA, extractors, integrations), especially in SAP-to-AWS migration projects.
  • Experience migrating legacy data platforms to the cloud.
  • AWS certifications (Data Engineer, Solutions Architect, or similar).
Interested? Apply now!