Senior Data Engineer
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Job Description
Senior Data Engineer building and optimizing data pipelines for real-time analytics at Dynatron. Collaborating with product and ML teams in a remote-first culture.
Responsibilities:
- Build and maintain complex data pipelines using AWS Glue, Step Functions, or Databricks Workflows.
- Implement modular data structures using advanced modeling techniques.
- Manage scalable data storage solutions using AWS S3 as the primary landing zone.
- Optimize storage formats and compute performance to ensure high-throughput processing.
- Build decoupled, event-driven architectures using AWS SNS and SQS.
- 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.
- 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.
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.
- Strong documentation habits 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:
- Competitive base salary
- 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
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