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Shape reliable, scalable data pipelines with Snowflake, AWS, Airflow, and dbt; collaborate across teams to turn data into actionable insights and AI-powered improvements. About The Role This role supports data-driven decision making by building reliable, scalable data pipelines and enabling analytics across the organization. You'll work with modern data stack tools to ensure strong engineering practices that support accuracy, reliability, and growth while collaborating closely with business stakeholders. What You'll Do Design, build, and maintain scalable data pipelines and ETL processes to support business analytics Perform data manipulation, transformation, and cleansing to ensure accuracy and integrity Develop and maintain database solutions using SQL Implement and optimize data models and storage solutions in Snowflake Leverage AWS services for data storage, processing, and analytics Use Terraform to manage and deploy cloud resources as infrastructure-as-code Orchestrate workflows and schedule pipelines using Apache Airflow Work with dbt (Data Build Tool) to develop, test, and maintain modular data transformations Create and maintain reports and dashboards in Looker Apply AI and machine learning concepts to improve data workflows, automation, and insights generation Use AI coding tools actively in daily development workflow to accelerate delivery Collaborate with the team to continuously improve data engineering practices and processes How You'll Succeed You deliver reliable, well-tested pipelines that scale with business growth You proactively identify data quality issues and implement solutions before they impact stakeholders You communicate technical concepts clearly and confidently in collaborative settings You balance speed with quality, knowing when to optimize and when to ship You share knowledge openly and help elevate team capabilities Who You Are Strong Python programming skills for data engineering tasks Proficiency in data manipulation and transformation Strong SQL skills for database management and querying Hands-on production experience with Apache Airflow for workflow orchestration Hands-on production experience with dbt for building scalable and maintainable data models Proficiency with Terraform for infrastructure automation Experience with AWS services for data engineering workloads Proficiency in Snowflake including administration experience Experience with Looker for reporting and dashboards Active daily use of AI coding tools (Claude Code, GitHub Copilot, or similar) in development workflow Exposure to AI concepts or tools applied to data workflows or analytics use cases Strong understanding of data modeling principles and best practices Excellent English communication skills. vocal, extroverted, and confident sharing ideas in collaborative settings Position Details Remote: Fully-remote Location: Latin America Your partner for AI, consulting, software development, and nearshore staffing.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.