Senior Data Engineer

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Dynatron Software, Inc.

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 1999

☁️ SaaS

Automotive • SaaS • Analytics

Dynatron Software, Inc. is a company that combines advanced analytics software with expert coaching to help automotive service departments maximize their revenue opportunities. Their product suite includes various solutions like PriceSmart for optimizing labor and part pricing, FileSmart for enhancing warranty labor rates and parts markup, SellSmart for increasing service sales to existing customers, and MarketSmart for boosting service department traffic through strategic marketing campaigns. With a focus on increasing profitability, Dynatron collaborates closely with dealerships to identify and capitalize on hidden revenue streams using their proprietary analytics and extensive repair order database.

📋 Description

• Build and maintain complex data pipelines using AWS Glue, Step Functions, or Databricks Workflows. • Implement modular data structures using advanced modeling techniques such as Medallion Architecture and Dimensional Modeling. • Manage scalable data storage solutions using AWS S3 as the primary landing zone and data lake foundation. • Optimize storage formats (Delta, Iceberg, Parquet) and compute performance to ensure high-throughput and cost-effective processing. • Develop and deploy real-time ingestion pipelines using AWS Kinesis or Kafka. • Own end-to-end data validation and QA by building automated data quality checks directly into the ETL/ELT pipelines. • Engineer ML-ready datasets and manage Feature Stores to support the Data Science team. • 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.

🎯 Requirements

• 6–8+ years of experience in data engineering with a focus on large-scale distributed systems. • Expert-level Python and PySpark with Strong SQL skills. • Deep hands-on experience with Snowflake or Databricks, built natively within 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 mindset. • Relevant IT professional certifications, such as SnowPro Core, Databricks Certified Data Engineer Professional, or AWS Certified Data Engineer (Nice-to-Have).

🏖️ Benefits

• Opportunity to build and scale the data foundation of a growing, AI-enabled SaaS company. • High-impact role supporting real-time analytics, machine learning, enterprise reporting, and product innovation. • Close partnership across Data, Product, Engineering, Analytics, and business leadership. • Values-driven culture built on accountability, urgency, and delivering measurable results. • Remote-first environment offering flexibility, autonomy, and trust.