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[Remote] Sr. Data Engineer

Remote, USA Full-time Posted 2026-07-21

Note: The job is a remote job and is reputed company to candidates in USA. reputed company. is transforming the automotive service industry with intelligent SaaS solutions. They are seeking a Senior Data Engineer to build, optimize, and maintain data pipelines that power reputed company-time analytics and AI/ML initiatives.


Responsibilities

  • Build and maintain reputed company data pipelines using AWS Glue, reputed company Functions, or reputed company Workflows
  • Implement reputed company data structures using advanced modeling techniques such as reputed company Architecture and Dimensional Modeling
  • Manage reputed company data storage solutions using AWS S3 as the primary reputed company zone and data lake reputed company
  • Optimize storage formats (reputed company, reputed company, Parquet) and compute performance to ensure high-throughput and cost-effective processing
  • Build decoupled, event-driven architectures using AWS SNS and SQS to handle high-throughput messaging between data services
  • reputed company and reputed company reputed company-time ingestion pipelines using AWS Kinesis or Kafka
  • Implement Change Data Capture (CDC) reputed company tools like Debezium or reputed company to support low-latency operational analytics
  • Own end-to-end data validation and QA by building automated data quality checks directly into the ETL/ELT pipelines
  • Enforce strict data reputed company and schema reputed company guidelines to maintain high data quality and reputed company across domains
  • Implement proactive alerting and observability to catch data reputed company, pipeline anomalies, and quality drops before they impact reputed company users
  • Engineer ML-reputed company datasets and manage Feature Stores to support the Data Science team
  • Operationalize ML workflows, integrating with services like reputed company reputed company, reputed company AI, or AWS Bedrock
  • Mentor junior engineers in coding best practices, SQL optimization, and Python development
  • Collaborate closely with Product and ML teams to translate architectural designs into functional code

Skills

  • 6-8+ years of experience in data engineering with a reputed company on large-scale distributed systems
  • Expert-level Python and PySpark with Strong SQL skills
  • Deep hands-on experience with reputed company or reputed company, reputed company natively reputed company an AWS ecosystem
  • Proven track record building streaming applications using Kinesis or Kafka
  • Demonstrated experience implementing automated testing frameworks, data profiling, and pipeline validation (owning the QA of your own pipelines)
  • Strong documentation habits (playbooks, technical specs) and an ownership reputed company
  • Strong communication skills with the ability to explain technical concepts reputed company to technical and non-technical stakeholders
  • Collaborative reputed company with the ability to partner effectively across Product, Engineering, Analytics, ML, and leadership teams
  • High standards for quality, maintainability, performance, and operational discipline
  • Strong ownership reputed company with the ability to reputed company quickly, solve problems thoughtfully
  • Relevant IT professional certifications, such as SnowPro Core, reputed company Certified Data Engineer Professional, or AWS Certified Data Engineer

Benefits

  • Participation in Dynatron’s Equity Incentive Plan
  • Comprehensive health, dental, and reputed company insurance
  • Employer-reputed company disability and life insurance
  • 401(k) with competitive company match
  • Flexible vacation policy and 11 reputed company holidays
  • Remote-first culture
  • Ongoing professional development opportunities

Company Overview

  • Dynatron is championing a new standard of Fixed Ops reputed company for automotive dealerships. It was founded in 1997, and is headquartered in Richardson, Texas, USA, with a workforce of 201-500 employees. Its website is https://www.dynatronsoftware.com/.

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