Requirements
- Bachelor's degree in Computer Science, Engineering, or a related field from an accredited university
- 7+ years of professional data engineering and/or backend software engineering experience
- Advanced SQL expertise across relational and NoSQL databases (SQL Server, Neo4j, Elasticsearch, Cosmos DB)
- Strong hands-on experience building and optimizing data pipelines on Azure Databricks
- In-depth knowledge of Delta Lake, Data Warehousing, and Lakehouse architecture
- Highly proficient in Spark, Python, and SQL
- Proven experience designing and deploying microservices on AKS using Docker, Kubernetes, and Helm
- Hands-on experience with Azure DevOps YAML pipelines for CI/CD automation
- Experience with SSE or real-time streaming — event stream formatting, retry logic, connection management
- Strong grasp of async Python: asyncio, async/await, event loops
- Experience with message brokers: Kafka, Redis Streams, RabbitMQ, or similar
- Proven track record of processing and extracting value from large, complex, and disconnected datasets
- Excellent stakeholder management and communication skills across global, cross-functional teams
- Proven leadership skills with a strategic mindset and passion for driving innovation
Nice to Have
- Experience with Fivetran for data integration
- Familiarity with BI tools such as Power BI
- Experience building and deploying ML and feature engineering pipelines using MLflow
- Knowledge of Knowledge Graph development (e.g., Neo4j) and NLP-based analytics
- Familiarity with cloud-based AI/ML services and Generative AI tools
- Experience working in a compliance-based environment (building and deploying compliant software throughout the SDLC)
- Familiarity with API gateway configuration for streaming (NGINX, Kong, Azure API Gateway)
Benefits
- Competitive compensation
- Employee medical coverage
- Central office location
- Entrepreneurial environment, autonomy, and fast decisions
- Casual work environment
Work Arrangement
Hybrid
