Lead Data Engineer

About the job

Job Description Role Overview: We are looking for a strong, hands-on, highly autonomous Lead Data Engineer to design, build, and operate the Service Layer platform that powers enterprise Quote-to-Cash (QTC), customer lifecycle, and finance integrations across strategic enterprise applications. Alongside deep technical contribution, you will provide technical leadership to a team of engineers, driving solution design, engineering excellence, delivery execution, and operational support across multiple integration initiatives. You will be instrumental in building and evolving a cloud-native, event-driven integration platform based on AWS, Kafka, Go and Python, leveraging canonical data models, and asynchronous messaging, while leading the adoption of best practices for architecture, engineering standards, observability, security, and platform reliability. The platform processes high-volume business-critical events while providing end-to-end visibility, reliability, security, and scalability. This role requires deep expertise in distributed systems, event-driven architecture, microservices, data engineering, and cloud-native development. You will contribute to the design and implementation of Service Layer foundation capabilities including messaging, observability, orchestration, data migration, reconciliation, canonical data management, and operational tooling. Key responsibilities: • Own end-to-end technical delivery of key initiatives, ensuring solutions are delivered with quality, scalability, security, and operational readiness. • Lead and mentor a team of engineers, fostering technical excellence, knowledge sharing, and continuous improvement across the team. • Drive architecture and design decisions for event-driven integrations, canonical data models, orchestration frameworks, and platform capabilities. • Define and enforce engineering standards, secure-by-design principles, cloud best practices, data governance and non-functional requirements for resilience, scalability, and supportability. • Design, develop, and operate real-time event-driven integration services using Golang and Python. • Build and enhance the Service Layer platform that orchestrates Quote-to-Cash workflows across enterprise applications. • Design and implement canonical data models, transformation frameworks, validation rules, and integration contracts that standardize communication across multiple business systems. • Design and implement scalable Kafka-based event processing solutions with support for retries, idempotency, sequencing, replay, and fault recovery. • Design and implement large-scale ETL, migration, reconciliation, and data-quality solutions using AWS Glue, Step Functions, Snowflake, PostgreSQL, and ClickHouse. • Design and implement observability, monitoring, alerting, and operational dashboards to enable end-to-end workflow visibility and supportability. • Partner with Product Managers, Architects, Enterprise Data teams, and other cross-functional stakeholders to define technical roadmaps and execution plans. • Lead code reviews, design reviews, technical governance activities, and engineering best-practice adoption across the team. • Drive engineering standards covering software development lifecycle, CI/CD, security, observability, resiliency, and cloud-native architecture patterns. Must Have Skills: • Proven experience leading and mentoring engineering teams, including task planning, technical guidance, code reviews, and delivery management. • Strong experience driving architecture and design decisions for large-scale distributed systems and enterprise integration platforms. • Strong hands-on experience in Golang and Python for building scalable backend services, event-driven integrations, orchestration workflows, and data processing solutions. • Strong experience designing and building cloud-native applications on AWS, including AWS Lambda, API Gateway, S3, RDS/Aurora PostgreSQL, DynamoDB, SQS, SNS, EventBridge, IAM, CloudWatch, VPC, and related serverless architecture patterns. • Experience managing technical delivery across multiple concurrent initiatives while balancing business priorities, technical debt, and platform evolution. • Strong experience designing and operating event-driven and asynchronous systems using Kafka, AWS MSK, RabbitMQ, or equivalent messaging technologies. • Strong understanding of distributed systems architecture, including scalability, resiliency, fault tolerance, idempotency, retry patterns, dead-letter queues, message replay, and eventual consistency. • Strong experience with PostgreSQL, ClickHouse, relational databases, and NoSQL databases such as DynamoDB, including data modelling, query optimization, and performance tuning. • Hands-on experience designing and implementing RESTful APIs, integration services, and enterprise system interfaces using secure API design principles. • Experience building and enforcing canonical data models, data contracts, transformation layers, and validation frameworks for enterprise integrations. • Hands-on experience building and supporting high-availability, business-critical applications on AWS with strong focus on performance, reliability, and operational supportability. • Experience with CI/CD pipelines, automated testing, code quality, and secure software delivery practices, using tools such as GitLab CI, Jenkins, SonarQube, Trivy, Semgrep etc. • Experience with observability, monitoring, and operational analytics, using CloudWatch, Grafana, Datadog, Prometheus, OpenTelemetry, or equivalent platforms. • Strong understanding of cloud security and secure-by-design principles, including IAM, OAuth2, JWT authentication, encryption at rest and in transit, Secrets Manager, vulnerability management, audit logging, and compliance controls. • Strong problem-solving skills with experience in production support, incident management, root cause analysis, and performance optimization within large-scale distributed environments. Qualifications: • Bachelor's degree in Computer Science, Engineering, Information Technology, or related discipline. • 10+ years of software engineering experience, with at least 5+ years focused on cloud-native, data engineering, integration, or distributed platforms. • 2+ years of experience leading engineering teams or acting as technical lead for large-scale enterprise initiatives. • 5+ years building cloud-native solutions on AWS. • 5+ years of experience working with Golang, Python, AWS Service, and Kafka in production environments. • Proven experience designing, building, and operating highly available enterprise integration and event-driven platforms. Nice to have: • AWS certifications such as AWS Certified Data Engineer – Associate, AWS Certified Solutions Architect – Associate, AWS Certified Developer, or equivalent. • Experience in Quote-to-Cash, CRM, ERP, Customer Lifecycle Management, or Enterprise Data domains.

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