Data Engineer

Explore the Nearsure experienceJoin our close-knit LATAM remote team: Connect through fun activities like coffee breaks, tech talks, and games with your team-mates and management.Say goodbye to micromanagement We champion autonomy, open communication, and respect for diversity as our core values.Your well-being matters: Our People Care team is here from day one to support you with everything from time-off requests to wellness check-ins.Plus, our Accounts Management team ensures smooth, effective client relationships, so you can focus on what you do best.Ready to grow with us?Here's what we offer you by joining usCompetitive USD salary – We value your skills and contributions100% remote work – While you can work from anywhere, you're always welcome to connect with teammates and grow your network at our coworking spaces across LATAMPaid time off – Take the time you need according to your country's regulations, all while receiving your full salary. Rest, recharge, and come back strongerNational Holidays celebrated – Take time off to celebrate important events and traditions with loved ones, fully embracing your culture.Sick leave – Focus on your health without the stress. Take the necessary time to recover and feel better.Refundable Annual Credit – Spend it on the perks you love to enhance your work-life balanceTeam-building activities – Join us for coffee breaks, tech talks, and after-work gatherings to bond with your Nearsure family and feel part of our vibrant community.Birthday day off – Enjoy an extra day off during your birthday week to celebrate in style with friends and familyAbout the project:As a Senior Data Engineer, you will work with modern data technologies such as Apache Spark (PySpark or Spark), Apache Iceberg, and AWS services (S3, EMR, Athena, Glue), ensuring data quality, scalability, and operational excellence. Familiarity with orchestration tools (Airflow), CI/CD practices, and the ability to leverage AI-powered development assistants (e.g., GitHub Copilot) is essential.How you'll contributeDesign, develop, and maintain batch ETL/ELT pipelines and data workflows for large-scale datasets in AWS.Implement and optimize data lakehouse architectures using Apache Iceberg on S3, ensuring schema evolution, partitioning strategies, and table maintenance.Build and tune distributed data processing jobs with Apache Spark (PySpark or Spark) for performance and cost efficiency.Orchestrate workflows using Apache Airflow, including DAG design, scheduling, and SLA monitoring.Apply best practices in code quality, version control (Git/GitHub), and CI/CD for data engineering projects.Ensure data quality, security, and compliance through validation, monitoring, and governance frameworks (Glue Catalog, IAM, encryption).Collaborate with cross-functional teams (data scientists, analysts, architects) to deliver scalable and reliable data solutions.Contribute to the development and optimization of analytics applications, ensuring they are powered by well-structured, high-quality data pipelines.Continuously evaluate and adopt emerging technologies and AI-powered tools to improve productivity and maintain technical excellence.This would make you the ideal candidateBachelor's Degree in Computer Science, Engineering, or a related field.5+ Years of experience working in data engineering, designing and developing large-scale data solutions.5+ Years of experience working with Python for data manipulation, scripting, and integration tasks.5+ Years of experience working with SQL & DBMS (e.g., PostgreSQL, MySQL, SQL Server), data modeling (Star Schema, Snowflake Schema) and query tuning and optimization.3+ Years of experience working with Apache Spark (PySpark preferred).3+ Years of experience working building batch ETL/ELT pipelines for large-scale datasets.3+ Years of experience working with AWS data services (S3, Athena/Presto, Glue, Lambda, CloudWatch) in production.2+ Years of experience working with Apache Iceberg (table design, partition strategies, schema evolution, maintenance, ingestion pipelines into Apache Iceberg on S3).2+ Years of experience working with AWS EMR as the execution platform for big data workloads.2+ Years of experience working with orchestrating data workflows with Apache Airflow (DAG design, scheduling, backfills, SLAs).2+ Years of experience using Git/GitHub (branching strategies, Pull request reviews, CI/CD for data pipelines).Experience designing efficient ingestion pipelines into analytical systems.Proficiency in logging, auditing, and monitoring for data pipelines.Experience with data cleansing, validation, and transformation for analytical/reporting systems.Familiarity with data security and privacy practices.Solid understanding of cloud-native analytics architectures (data lake/lakehouse, ELT patterns).Proven ability to leverage AI-powered assistants (e.g., GitHub Copilot, AI coding agents) as part of the engineering workflow, demonstrating comfort and efficiency in using these tools to accelerate delivery and maintain code quality.Advanced English Level is required for this role, as you will work with US clients. Effective communication in English is essential to deliver the best solutions to our clients and expand your horizons.What to expect from our hiring process1. Let's chat about your experience2. Impress our recruiters, and you'll move on to a technical interview with our top developers.3. Nail that, and you'll meet our client - your final step to joining our amazing teamAt Nearsure, we're dedicated to solving complex business challenges through cutting-edge technology and we believe in the power of tailored solutions. Whether you are passionate about transforming businesses with Generative AI, building innovative software products, or implementing comprehensive enterprise platform solutions, we invite you to be part of our dynamic teamWe would love to hear from you if you are eager to make an impact and join a collaborative team that values creativity and expertise.Let's work together to shape the future of technologyApply nowBy applying to this position, you authorize Nearsure to collect, store, transfer, and process your personal data in accordance with our Privacy Policy. For more information, please review our Privacy Policy. (