Job Description
Job Description
Senior Data Engineer 7 Years of Experience
- We are seeking a highly experienced Senior Data Engineer with 7 years of expertise in designing, building, and optimizing robust data solutions. The ideal candidate must possess top-tier skills in Python, AWS services, API development, and TypeScript, and have significant hands-on experience with anomaly detection systems.
- The candidate should have a proven ability to work at both strategic and tactical levels, from designing data architectures to implementing them in the weeds.
Required Technical Skills : Python, SQL, TypeScript, AWS Web services, Swagger / Open AI, Rest API, LLM / AI, Graphql
Core Programming Skills :
Expert proficiency in Python , with experience in building data pipelines and back-end systems.Solid experience with TypeScript for developing scalable applications.Advanced knowledge of SQL for querying and optimizing large datasets.AWS Cloud Services Expertise :
DynamoDB , S3 , Athena , GlueETL , Lambda , ECS , Glue Data Quality , EventBridge , Redshift Machine Learning , OpenSearch , and RDS .API and Resilience Engineering :
Proven expertise in designing fault-tolerant APIs using Swagger / OpenAPI , GraphQL , and RESTful standards.Strong understanding of distributed systems, load balancing, and failover strategies.Monitoring and Orchestration :
Hands-on experience with Prometheus and Grafana for observability and monitoring.Key Responsibilities :
Data Pipeline Development
Independently design, build, and maintain complex ETL pipelines, ensuring scalability and efficiency for large-scale data processing needs.Manage pipeline complexity and orchestration, delivering high-performance data products accessible via APIs for business-critical applications.Archive processed data products into data lakes (e.g., AWS S3) for analytics and machine learning use cases.Anomaly Detection and Data Quality
Implement advanced anomaly detection systems and data validation techniques, ensuring data integrity and quality.Leverage AI / ML methodologies, including Large Language Models (LLMs), to detect and address data inconsistencies.Develop and automate robust data quality and validation frameworks.Cloud and API Engineering
Architect and manage resilient APIs using modern patterns, including microservices, RESTful design, and GraphQL.Configure API gateways, circuit breakers, and fault-tolerant mechanisms for distributed systems.Ensure horizontal and vertical scaling strategies for API-driven data products.Monitoring and Observability
Implement comprehensive monitoring and observability solutions using Prometheus and Grafana to optimize system reliability.Establish proactive alerting systems and ensure real-time system health visibility.Cross-functional Collaboration and Innovation
Collaborate with stakeholders to understand business needs and translate them into scalable, data-driven solutions.Continuously research and integrate emerging technologies to enhance data engineering practices.Required Skills : Python
Basic Qualification :
Additional Skills :
Background Check : No
Drug Screen : No
