Jobgether

Compensation

Full Description

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Data Engineer in the United States. We are seeking an experienced Data Engineer to join a fully remote team focused on modernizing and optimizing data pipelines and analytics infrastructure. In this role, you will work closely with cross-functional teams, including Cloud Architects, analysts, and DevOps, to design and implement scalable ETL solutions in cloud environments. You will play a key role in migrating and improving existing workflows while ensuring high-quality, secure, and efficient data processing. This position offers the opportunity to take ownership of technical initiatives, influence architecture decisions, and contribute to a culture of innovation and continuous improvement. If you are passionate about cloud technologies, ETL development, and translating complex data into actionable insights, this role provides a dynamic and collaborative environment. Accountabilities Design, implement, and maintain ETL pipelines using AWS Glue and PySpark. Migrate and re-architect existing ETL solutions from legacy platforms, including Databricks and Linux/Python scripts. Collaborate with Cloud Architects and DevOps to modernize data ingestion and processing patterns. Perform data modeling, transformation, and validation to support analytics and reporting. Troubleshoot and debug pipeline failures while optimizing performance and scalability. Develop custom reports, complex queries, and automation scripts to support stakeholders. Ensure compliance with SDLC processes and maintain secure, auditable data pipelines. Support DevSecOps initiatives, including infrastructure setup, security remediation, and CI/CD deployment. U.S. citizenship or authorization to work with at least 3 of the last 5 years residing in the U.S. Bachelor’s degree (or equivalent experience) with 5+ years in data engineering or related roles. Strong experience with cloud platforms, especially AWS, and ETL tools such as AWS Glue. Proficient in Python and/or PySpark for data processing tasks. Experience with semi-structured data formats (XML, JSON, Parquet) and relational databases. Knowledge of Snowflake cloud data platform, including performance tuning and optimization. Familiarity with CI/CD tools, version control (GitHub), and Agile development practices. Understanding of database security, audit, and access controls. Strong problem-solving, analytical, and communication skills, with the ability to collaborate across technical teams. Ability to obtain Public Trust clearance. Competitive salary range ($93,000–$149,100/year) with discretionary bonuses. Comprehensive health, dental, and retirement benefits. Professional development and educational opportunities. Fully remote work with flexible schedule options. Opportunities to work on innovative cloud-based data solutions and contribute to cross-functional projects. Supportive, collaborative, and growth-oriented work environment. Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching. When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly: 🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements. 📊 It compares your profile to the job’s core requirements and past success factors to determine your match score. 🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role. 🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed. The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team. Thank you for your interest! #LI-CL1