Note: The job is a remote job and is open to candidates in USA. Dynatron is an AI-enabled SaaS company that provides an AI-powered Fixed Ops Data Intelligence Platform for automotive dealerships. The Data Engineer will build, optimize, and maintain scalable AWS-based data pipelines and data ecosystems supporting real-time analytics, AI/ML initiatives, and enterprise reporting, while owning data quality, validation, observability, and ML workflow integration.
Responsibilities
- 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
- Build decoupled, event-driven architectures using AWS SNS and SQS to handle high-throughput messaging between data services
- Develop and deploy real-time ingestion pipelines using AWS Kinesis or Kafka
- Implement Change Data Capture (CDC) via tools like Debezium or Fivetran 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 contracts and schema evolution guidelines to maintain high data quality and integrity across domains
- Implement proactive alerting and observability to catch data drift, pipeline anomalies, and quality drops before they impact downstream users
- Engineer ML-ready datasets and manage Feature Stores to support the Data Science team
- Operationalize ML workflows, integrating with services like Snowflake Cortex, Databricks AI, or AWS Bedrock
- Adhere to coding best practices, SQL optimization, and Python development
- Collaborate closely with Product and ML teams to translate architectural designs into functional code
- Participate in a rotation to monitor pipeline health and respond to production data issues outside of core hours as needed
Skills
- * Experience: 5+ years of experience in data engineering with a focus on large-scale distributed systems
- * Core Languages: Expert-level Python and PySpark with Strong SQL skills
- * Platforms: Deep hands-on experience with Snowflake or Databricks, built natively within an AWS ecosystem
- * Streaming: Proven track record building streaming applications using Kinesis or Kafka
- * Data Validation: Demonstrated experience implementing automated testing frameworks, data profiling, and pipeline validation (owning the QA of your own pipelines)
- * Soft Skills: Strong documentation habits (playbooks, technical specs) and an ownership mindset
- * Strong communication skills with the ability to explain technical concepts clearly to technical and non-technical stakeholders
- * Collaborative mindset 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 mindset with the ability to move quickly, solve problems thoughtfully
- * Certifications (Nice-to-Have): Relevant IT professional certifications, such as SnowPro Core, Databricks Certified Data Engineer Professional, or AWS Certified Data Engineer
Benefits
- Participation in Dynatron’s Equity Incentive Plan
- Comprehensive health, dental, and vision insurance
- Employer-paid disability and life insurance
- 401(k) with competitive company match
- Flexible vacation policy and 11 paid holidays
- Remote-first culture
- Ongoing professional development opportunities
Company Overview