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Senior Data Engineer
Dynatron Software, Inc.Senior Data Engineer managing data pipelines, optimizing data lakes, and collaborating with AI/ML teams at Dynatron. Focused on building robust data ecosystems and ensuring high data quality and performance.
Tech Stack
Tools & technologiesAWSDistributed SystemsETLKafkaPySparkPythonSQL
About the role
Key responsibilities & impact- 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
What you’ll need- 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
Comp & perks- 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.
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Data EngineeringETLData ValidationDimensional ModelingStreaming ApplicationsData ProfilingFeature StoresModular Data StructuresAutomated Testing FrameworksSQL Optimization
Soft Skills
MentoringDocumentationOwnership Mindset
Certifications
SnowPro CoreDatabricks Certified Data Engineer ProfessionalAWS Certified Data Engineer