Sr. Data Engineer
Dynatron Software•Richardson, TX
•Remote
About The Position
Dynatron is seeking a highly skilled Senior Data Engineer to join our growing data team. While our architects define the blueprint, you will be the lead craftsman responsible for building, optimizing, and maintaining the robust data pipelines that power our real-time analytics, AI/ML initiatives, and enterprise reporting. You are a hands-on expert in AWS and modern cloud data stacks, specifically Snowflake or Databricks, and possess the engineering rigor to build scalable, production-grade data ecosystems.
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.
- 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.
Nice To Haves
- Relevant IT professional certifications, such as SnowPro Core, Databricks Certified Data Engineer Professional, or AWS Certified Data Engineer.
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.
- 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.
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
- Ongoing professional development opportunities
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
