Data Engineer

A Leading Technology Services Firm is seeking a highly autonomous Data Engineer to design and build cloud-native integration platforms.

The Data Engineer must combine deep expertise in distributed systems and event-driven architecture with hands-on Golang, Python, AWS, and Kafka engineering.

Key Responsibilities

• Lead technical architecture, solution design, and delivery execution for enterprise Quote-to-Cash (QTC) integration services.
• Design, develop, and operate high-throughput, real-time event-driven microservices using Golang and Python.
• Architect scalable Kafka and AWS MSK event processing workflows supporting idempotency, replay mechanisms, and fault recovery.
• Build and maintain canonical data models, integration contracts, validation frameworks, and data transformation layers.
• Implement large-scale ETL, data migration, and reconciliation pipelines using AWS Glue, Step Functions, Snowflake, ClickHouse, and PostgreSQL.
• Establish platform observability, distributed tracing, and automated monitoring dashboards using CloudWatch, Prometheus, and Grafana.
• Enforce engineering excellence, secure-by-design principles, automated CI/CD pipelines, and cloud governance standards.
• Mentor and guide software engineers through structured design reviews, code quality checks, and architectural discussions.

Requirements and Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related discipline.
• 8+ Years of software engineering experience, with at least 4+ years dedicated to cloud-native data engineering and distributed systems.
• Hands-on production proficiency in Golang, Python, and enterprise AWS services (Lambda, DynamoDB, RDS, SQS, EventBridge).
• Proven track record building event-driven streaming solutions using Apache Kafka, AWS MSK, or RabbitMQ.
• Solid expertise with relational and columnar databases, including PostgreSQL and ClickHouse, covering schema optimization and query tuning.