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Data Engineer

57 minutes ago
Argentina, Brazil, Costa Rica
Full-time
Mid Level
Data Engineer
Software Development
Apache Airflow AWS Azure CI/CD CloudFormation Dagster dbt Docker GCP GitHub Actions GitLab CI HIPAA Jenkins Kafka Kubernetes Looker Power BI Prefect Python Scala Snowflake SQL Tableau Terraform
Apply Now
Pavago

Pavago

Pavago specializes in connecting small and medium-sized businesses with skilled offshore talent from Pakistan and Latin America, offering a streamlined recruitment process that enables the hiring, onboarding, and payment of remote employees at signific...

IT Services
Founded 2023
View All Jobs 60

Description

  • Build, maintain, and optimize ETL/ELT pipelines using Python, SQL, or Scala.
  • Orchestrate data workflows using Airflow, Prefect, Dagster, or similar tools.
  • Ingest structured and unstructured data from APIs, SaaS platforms, databases, files, and streaming systems.
  • Manage and optimize cloud data warehouses such as Snowflake, BigQuery, or Redshift.
  • Design scalable schemas and build analytics-ready datasets for BI and reporting use cases.
  • Implement data validation, anomaly detection, logging, monitoring, and other reliability checks.
  • Maintain naming conventions, lineage tracking, documentation, and audit-ready data processes.
  • Build and manage real-time data pipelines and support event-driven architectures for time-sensitive applications.
  • Partner with analysts, data scientists, and business stakeholders to deliver trustworthy datasets.
  • Automate deployments and manage supporting infrastructure with Docker, Kubernetes, CI/CD, and Infrastructure-as-Code tools.

Requirements

  • 3+ years of experience in Data Engineering, Back-End Engineering, or Data Infrastructure roles.
  • Strong proficiency in Python and SQL.
  • Experience with at least one modern data warehouse, such as Snowflake, Redshift, or BigQuery.
  • Hands-on experience with orchestration tools such as Airflow or Prefect.
  • Strong understanding of ETL/ELT pipelines, data modeling, and data transformation workflows.
  • Familiarity with cloud platforms such as AWS, GCP, or Azure.
  • Experience with dbt for data modeling and transformation management is preferred.
  • Streaming and event-driven data pipeline experience with Kafka, Kinesis, or Pub/Sub is preferred.
  • Familiarity with Docker, Kubernetes, Terraform, or CI/CD workflows is preferred.
  • Background in regulated industries such as healthcare, fintech, or enterprise SaaS is preferred.

Benefits

  • Full-time remote position.
  • Flexible working hours aligned to U.S. client business hours, with flexibility for pipeline monitoring, deployments, and data refresh cycles.

Interested in this position?

Apply directly on the company website

Apply Now

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