Data Engineer (Cloud Native)

Tasks:

- Design, Develop and Maintain of a modular and scalable data architecture

- Efficient Data Modeling and ensuring of robust data integration

- Drive application migration to cloud native infrastructure

- Ensure consistent documentation

Skills (must-have):

- A minimum experience of 5 years in Cloud Native Data Engineering.

- Experience with rearchitecting existing monolithic architecture to micro-services based Cloud Native architectures.

- Strong understanding of Cloud Native architectures (loosely coupled services, containers, horizontal scalability, application resilience patterns).

- Proficiency in at least one programming language – Java or Scala

- Knowledge and experience with at least some of the Data technologies/frameworks:

o Workflow orchestration (AirFlow/Oozie etc.)

o Data integration/Ingestion (Nifi, Flume etc)

o Messaging/Data Streaming (Kafka/RabbitMQ etc.)

o Data Processing (Spark, Flink etc.)

o RDBMS (PostgreSQL/MySql etc.)

o NoSQL Storages (MongoDB, Cassandra, Neo4j etc.)

o Timeseries (InfluxDB, OpenTSDB, TimescaleDB, Prometheus etc.)

- And / Or with their Cloud provided counterparts, i.e., Cloud Data/Analytics services (GCP, Azure, AWS)

- Proficiency in the following Tech Stack:

- Deployment & Containerization: Docker, Kubernetes, Helm.

- CI/CD & DevOps Tools: Azure DevOps, Gitlab CI Actions, GitOps, Gitlab, Bash/Shell scripting, Linux

- Database change management: tools (such as Liquibase or Flyway)

- Familiarity with agile development methodologies and tools (e.g., Scrum, SAFE, JIRA, Confluence).

Skills (should-have):

- Relevant certifications in cloud and Cloud Native technologies