Senior Data Engineer (Remote - US) at Jobgether

, , United States -

Full Time

Start Date

Immediate

Expiry Date

11 Jan, 26

Salary

158100.0

Posted On

13 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Data Pipelines, SQL, Snowflake, Informatica, Data Ingestion, Data Transformation, Data Validation, Data Orchestration, Programming, Problem-Solving, Analytical Skills, Collaboration, Continuous Integration, Deployment Practices, Mentoring

Industry

Internet Marketplace Platforms

Description

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Data Engineer in the United States. We are seeking a Senior Data Engineer to design, develop, and operationalize high-performance data pipelines that enable analytics and reporting across large-scale environments. This role involves managing data ingestion, transformation, validation, and orchestration, ensuring data reliability, quality, and efficiency. You will collaborate with cross-functional teams, including DevSecOps, to implement continuous integration and deployment practices. The ideal candidate brings deep expertise in data architecture and programming, and thrives in a dynamic, fast-paced environment where innovation and automation are encouraged. You will guide junior engineers, optimize existing systems, and contribute to shaping the organization’s data strategy. Accountabilities Design, develop, and maintain scalable data pipelines and real-time processing applications. Ensure data quality, consistency, and reliability across multiple environments. Collaborate with DevSecOps and other teams to integrate CI/CD practices. Guide data engineers in the design, implementation, and operation of large-scale data structures for analytics. Identify opportunities to automate data workflows and improve efficiency. Document procedures, architectures, and best practices for data management. Monitor and optimize data processing performance and implement improvements. Bachelor’s degree in a quantitative or technical field (e.g., Statistics, Mathematics, Engineering, Computer Science) or equivalent experience. 4–6 years of experience in data engineering or related roles. Proficiency in one or more of the following technologies: SQL Snowflake Informatica Experience with data ingestion, transformation, validation, and orchestration. Strong programming skills and familiarity with advanced data processing tools. Ability to guide and mentor junior team members. Strong problem-solving, analytical, and collaboration skills. Familiarity with continuous integration and deployment practices. Competitive salary range: $85,300 - $158,100 per year. Comprehensive health insurance plans. 401K and stock purchase options. Tuition reimbursement and professional development opportunities. Paid time off and holidays. Flexible work arrangements: remote, hybrid, field, or office schedules. Inclusive and supportive workplace culture. 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. This process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, it is shared directly with the hiring company, who will manage the final selection steps, including interviews and additional assessments. Thank you for your interest! #LI-CL1

Responsibilities

Design, develop, and maintain scalable data pipelines and real-time processing applications. Ensure data quality, consistency, and reliability across multiple environments.