Senior Data Engineer (Brickman)

ZipRecruiter; Malvern Hills; On-site; GBP 50,000 - 90,000

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 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.