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Data Engineer

1 hour, 14 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 with tools such as Airflow, Prefect, or Dagster.
  • Ingest structured and unstructured data from APIs, SaaS platforms, databases, files, and streaming systems.
  • Design and optimize cloud data warehouse structures in Snowflake, BigQuery, or Redshift.
  • Develop scalable schemas and implement partitioning, clustering, indexing, and other performance improvements.
  • Create clean, analytics-ready datasets for business intelligence, reporting, and downstream applications.
  • Implement data quality checks, monitoring, anomaly detection, logging, and validation processes.
  • Maintain lineage, documentation, and audit-ready data processes, including compliance-related requirements.
  • Build and support real-time streaming pipelines using Kafka, Kinesis, Pub/Sub, or similar platforms.
  • Collaborate with analysts, data scientists, and business stakeholders to translate requirements into data solutions.

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.
  • Experience with cloud-native data services such as AWS Glue, GCP Dataflow, or Azure Data Factory 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.
  • Experience optimizing warehouse costs and query performance at scale is preferred.

Benefits

  • Full-time remote position.
  • Working hours aligned to U.S. client business hours with flexibility for pipeline monitoring, deployments, and data refresh cycles.
  • Opportunity to work on scalable data infrastructure supporting analytics, reporting, and operational decisions.
  • Exposure to modern data stack tools and cloud data platforms.
  • Interview process includes a technical assessment and team interviews.

Interested in this position?

Apply directly on the company website

Apply Now

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