About the Role
You will build, operate, and maintain production data pipelines and cloud-native data solutions. You will design scalable batch and streaming systems, implement transformations and tests with dbt, orchestrate workflows with Airflow, and optimize Databricks and Spark workloads. You will write clean, well-tested code, troubleshoot production issues, improve system performance and reliability, and collaborate closely with product, analytics, and infrastructure teams. You will also leverage AI tools to improve productivity and adopt automation where appropriate.
Requirements
- Bachelor's or Master's degree in Computer Science Engineering or related field
- 5+ years of professional experience in data engineering or distributed systems
- Strong hands-on coding experience in Python Java or similar languages
- Experience building and operating both batch and streaming data pipelines
- Strong experience with AWS Databricks and Spark and modern data architectures
- Hands-on experience with dbt for transformations and Airflow or similar for orchestration
- Solid understanding of data modeling data quality and production data systems
- Experience working with relational and non-relational databases such as Postgres and SQL Server
- Familiarity with CI/CD testing frameworks and monitoring tools
Responsibilities
- Partner across business lines to build and enhance a reliable and scalable data platform
- Design build and maintain scalable data pipelines for batch and streaming workloads
- Develop and operate high-throughput low-latency data processing systems
- Support and optimize Databricks and Spark ecosystems for large-scale data workloads
- Build and maintain cloud-native data solutions on AWS
- Implement transformations data modeling testing and documentation using dbt
- Manage orchestration and scheduling of data workflows using Airflow or similar tools
- Write clean efficient and well-tested code following software engineering best practices
- Collaborate with product analytics and infrastructure teams to deliver impactful data solutions
- Contribute to technical design discussions to improve performance scalability and reliability
- Support production systems by troubleshooting incidents and implementing improvements
- Leverage AI tools and automation platforms to improve team productivity and output quality
Benefits
- Flexible time off
- Hybrid working arrangements
- Company-paid health and protective benefits for employees and eligible dependents
- Coaching and counseling sessions through Headspace
- Paid parental leave
- Free daily snacks and weekly lunches
- Employee Resource Groups