Data Engineer (AWS, SQL)

The Opportunity: We are seeking a highly experienced Data Engineer to join our MarTech team and play a pivotal role in driving innovation within our microservices architecture, with a strong emphasis on data engineering and back-end systems. You will be responsible for leading the development, optimization, and maintenance of both data pipelines and back-end services, ensuring seamless integration within a microservices environment. You'll be responsible for building robust data solutions and crafting the APIs and services that power the customer experience. This role demands a strong understanding of microservices principles, data engineering best practices, back-end development, and experience with building scalable solutions.

Responsibilities:
Lead the design, development, and deployment of data engineering solutions and back-end services within a microservices environment.
Architect and implement scalable data pipelines for ingestion, processing, and storage of data from various sources, ensuring data quality and reliability.
Design, code, configure, test, debug, deploy, document, and maintain both data pipelines and back-end web service applications using a variety of software development toolkits, testing/verification applications and other tools, while adhering to specific development best practices and quality standards.
Work closely with solution engineers and architects to develop technical design specifications from which programs will be written or configured, with a strong focus on microservices integration for both data and application components.
Validate that proposed back-end services and data solutions align with both the architectural design and the business needs, ensuring seamless integration within the existing microservices environment.
Responsible for troubleshooting and issue analysis across the back-end stack, including data pipelines, microservices, and APIs, as well as coding, testing, and implementing software enhancements.
Implement and maintain data governance and API governance policies and standards across the microservices landscape.
Collaborate with cross-functional teams to define data requirements, design APIs, and deliver data-driven services.
Available to support/unblock planned deployments during off hours.
Contribute to the evolution of our data and application architecture, with a focus on microservices best practices, data engineering principles, and emerging technologies.
Lead and mentor other engineers, fostering a culture of innovation and collaboration across both data engineering and back-end development.

We are excited about you if you have experience with the following technologies:
Git, CI/CD, Jenkins, ArgoCD
Scala/Java, SQL/SparkSQL, Python
Apache Spark, Databricks, Apache Storm
Cosmos DB, Redis,
Maven, Gradle Build Tools
Kafka Ecosystem, Kafka Streams library, Kafka Avro Schemas
Cosmos DB, Redis Cache and Redis Insight Tool
Grafana, Grafana Loki Logging
Restful API Design Patterns, Swagger Documentation
Experience with markup languages such as JSON and YAML
Proven experience designing and implementing microservices architectures.
Strong understanding of data modeling, data warehousing, and ETL processes.
Experience with containerization technologies such as Docker and Kubernetes.
Experience with cloud platforms (e.g., AWS, Azure, GCP) and their data engineering and back-end services.
Experience with Node.js.
Familiarity with Rust is a plus.