Senior Data Engineer
New
D
DynatronAutomotive SaaS
USAFull-TimeSenior
SalaryCompetitive base salary, Participation in Dynatron’s Equity Incentive Plan
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Job Details
- Experience
- 6-8+ years
- Required Skills
- AWSPythonSQLSnowflakeApache KafkaData modelingDatabricksPySpark
Requirements
- 6-8+ years of experience in data engineering with a focus on large-scale distributed systems.
- Expert-level proficiency in Python and PySpark.
- 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 including playbooks and technical specs.
- Ownership mindset with high standards for quality and performance.
Responsibilities
- Build and maintain complex data pipelines using AWS Glue, Step Functions, or Databricks Workflows.
- Implement modular data structures using Medallion Architecture and Dimensional Modeling.
- Manage scalable data storage solutions using AWS S3, Delta, Iceberg, and Parquet.
- Build decoupled, event-driven architectures using AWS SNS and SQS.
- Develop and deploy real-time ingestion pipelines using AWS Kinesis or Kafka.
- Implement Change Data Capture (CDC) via Debezium or Fivetran.
- Own end-to-end data validation and automated QA within ETL/ELT pipelines.
- Engineer ML-ready datasets and manage Feature Stores to support Data Science.
- Mentor junior engineers in coding best practices and SQL optimization.
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