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Senior Data Engineer (AWS)

Role overview

Qualifications

  • 5+ years of professional experience in Data Engineering roles
  • Proficiency with Python, advanced SQL, dbt Cloud, Snowflake, Terraform, and Docker
  • Deep hands-on experience with core AWS data services (S3, Glue, Athena, EventBridge, AppFlow, DMS)
  • Advanced English (written and spoken) is mandatory

Responsibilities

  • Design and own the architectural evolution of data pipelines and platform components
  • Build and maintain robust ingestion pipelines leveraging AWS DMS, Amazon AppFlow, and Amazon EventBridge
  • Optimize and model analytics datasets within dbt Cloud, applying strict dimensional modeling
  • Collaborate with cross-functional teams to prepare curated datasets for Power BI

About the company

CodeRoad Inc logo

CodeRoad Inc

Software Development

Unknown

Company details

IndustrySoftware Development
Company sizeUnknown

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Job description

 

AWS Data Engineer

Latin America | 100% Remote

About CodeRoad

CodeRoad provides end-to-end software development services, helping businesses scale with ideal infrastructure solutions. From staff augmentation to dedicated IT teams and general software engineering, our nearshore technology services empower businesses to thrive in an ever-evolving digital landscape

 

About the Role

We are looking for a Mid-to-Senior Data Engineer to architect, build, and operate cloud-native data pipelines on AWS. In this role, you will anchor the flow of data from diverse source systems—including relational databases, SaaS applications, and event streams—into a central Snowflake data platform modeled in dbt Cloud. You will be responsible for ensuring technical excellence across our data infrastructure by writing production-grade Python, utilizing modern AI coding assistants like GitHub Copilot and Claude, and managing infrastructure as code via Terraform.

 

This role is critical to shaping and defending our core data architecture, optimizing platform performance, and delivering curated, analytics-ready datasets for downstream BI and reporting. As a key contributor on a fully remote team, your autonomy, ownership mindset, and clear written communication will directly impact our ability to scale data solutions and maintain full historical accuracy using advanced dimensional modeling techniques.

Key Responsibilities

  • Design and own the architectural evolution of data pipelines and platform components, leading design reviews and defending technical decisions with evidence-based reasoning.

  • Build and maintain robust ingestion pipelines leveraging AWS DMS, Amazon AppFlow, and Amazon EventBridge to land data seamlessly into AWS S3 and Snowflake.

  • Optimize and model analytics datasets within dbt Cloud, applying strict dimensional modeling (Kimball techniques) and implementing SCD Type 2 logic.

  • Lead performance tuning and cost optimization efforts across the Snowflake ecosystem, proactively implementing monitoring, alerting, and root-cause analysis.

  • Collaborate with cross-functional teams to prepare curated datasets for Power BI, while mentoring peers through rigorous code reviews and engineering enablement.

Requirements

  • Years of Experience: 5+ years of professional experience in Data Engineering roles.

  • Tech Stack: Proficiency with Python (including AWS Lambda), advanced SQL, dbt Cloud, Snowflake, Terraform (IaC), and Docker.

  • Cloud Infrastructure: Deep hands-on experience with core AWS data services (S3, Glue, Athena, EventBridge, AppFlow, DMS).

  • Data Modeling: Solid grasp of dimensional modeling (star schemas, fact/dimension design) and practical implementation of SCD Type 2.

  • Soft Skills: High autonomy, ownership mindset, discipline to raise risks early, and comfort utilizing AI-assisted development tools (GitHub Copilot, Claude).

  • Language: Advanced English (written and spoken) is mandatory for seamless remote collaboration.

Nice to Have

  • AWS Certified Data Engineer – Associate (DEA-C01) or equivalent certification.

  • Experience with change-data-capture (CDC) and near-real-time ingestion patterns.

  • Exposure to workflow orchestration tools such as Apache Airflow, Dagster, or Prefect.

  • Familiarity with data observability frameworks (Great Expectations, Monte Carlo) and open table formats like Apache Iceberg.

What You’ll Love

 

  • 100% Remote

  • Holidays off

  • Paid Time Off

  • Health insurance assistance

  • Competitive USD compensation

  • Growth opportunities

 

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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