About the Role
As a Data Engineer, you will design and build scalable data pipelines, warehouses, and real-time processing systems that form the backbone of our analytics and AI capabilities. You'll collaborate with data scientists, analysts, and product teams to ensure high-quality, reliable data flows from dozens of sources into actionable insights. Your work will directly influence how the organization makes decisions at every level.
Key Responsibilities
- Design and maintain scalable ETL/ELT pipelines that process terabytes of data daily with high reliability
- Architect data warehouse schemas optimized for analytics, reporting, and machine learning workloads
- Build real-time streaming solutions using Kafka, Spark Streaming, or Flink for event-driven architectures
- Implement data quality frameworks including validation, monitoring, and anomaly detection systems
- Optimize query performance and storage costs across cloud data platforms and distributed databases
- Create comprehensive documentation, data catalogs, and lineage tracking for all data assets
Requirements
- 3+ years of professional experience in data engineering or a closely related data-intensive role
- Advanced SQL skills and strong proficiency in Python for data processing and automation
- Hands-on experience with Apache Spark, Airflow, or equivalent orchestration and processing tools
- Familiarity with cloud data services (AWS Redshift, GCP BigQuery, Azure Synapse, or Snowflake)
- Strong understanding of data modeling concepts including star schema, normalization, and slowly changing dimensions
- Analytical mindset with excellent problem-solving skills and attention to data accuracy
What We Offer
Competitive Salary
$110K – $160K base, plus equity and performance bonuses
Health Insurance
Full medical, dental, and vision plans for you and your dependents
Learning Budget
$2,500 annual budget for certifications, courses, and conferences
Remote Work
Flexible hybrid model with the option to work fully remote
Join a team that values innovation