Purple Drive
Key Responsibilities
Design, develop, and maintain
scalable backend services and APIs
using
Java, Python, Scala, Node.js, and GraphQL . Architect and implement
big data solutions
leveraging
Hadoop, Hive, Spark (Scala), Presto/Trino, and Data Lake concepts . Develop and optimize
data processing and streaming pipelines
using
Storm, Spark Streaming, Airflow, Luigi, and Automic . Collaborate with data scientists and ML engineers to integrate solutions with
Vertex AI
and other cloud-based AI/ML platforms. Implement containerized solutions with
Docker & Kubernetes
and manage deployment on
cloud environments (AWS/GCP/Azure) . Ensure
system reliability, scalability, and performance
through monitoring, testing, and optimization. Partner with cross-functional teams including product managers, data engineers, and DevOps to deliver high-quality solutions. Troubleshoot production issues, optimize system performance, and ensure data consistency and security. Required Skills & Qualifications
Bachelor's/Master's degree
in Computer Science, Engineering, or related field (or equivalent practical experience). 7-10 years
of experience in backend and data engineering. Proficiency in
Java, Python, Scala, and Node.js
for backend and API development. Strong experience with
GraphQL (GQL)
schema design and implementation. Expertise in
Hadoop ecosystem (HDFS, Hive, Spark with Scala) . Hands-on experience with
Presto/Trino
and
Data Lake architectures . Practical knowledge of
stream-processing frameworks
such as
Storm and Spark Streaming . Experience with
orchestration & workflow tools : Airflow, Luigi, Automic. Proficiency with
Kubernetes
and containerized deployments. Strong understanding of
cloud services
(GCP/AWS/Azure) and
Vertex AI . Excellent problem-solving, debugging, and optimization skills. Preferred Skills (Nice to Have)
Experience with
machine learning integration
and MLOps workflows. Knowledge of
NoSQL databases
(MongoDB, Cassandra, etc.). Exposure to
observability/monitoring tools
(Grafana, Prometheus, ELK, etc.). Familiarity with
Agile/Scrum methodologies .
Design, develop, and maintain
scalable backend services and APIs
using
Java, Python, Scala, Node.js, and GraphQL . Architect and implement
big data solutions
leveraging
Hadoop, Hive, Spark (Scala), Presto/Trino, and Data Lake concepts . Develop and optimize
data processing and streaming pipelines
using
Storm, Spark Streaming, Airflow, Luigi, and Automic . Collaborate with data scientists and ML engineers to integrate solutions with
Vertex AI
and other cloud-based AI/ML platforms. Implement containerized solutions with
Docker & Kubernetes
and manage deployment on
cloud environments (AWS/GCP/Azure) . Ensure
system reliability, scalability, and performance
through monitoring, testing, and optimization. Partner with cross-functional teams including product managers, data engineers, and DevOps to deliver high-quality solutions. Troubleshoot production issues, optimize system performance, and ensure data consistency and security. Required Skills & Qualifications
Bachelor's/Master's degree
in Computer Science, Engineering, or related field (or equivalent practical experience). 7-10 years
of experience in backend and data engineering. Proficiency in
Java, Python, Scala, and Node.js
for backend and API development. Strong experience with
GraphQL (GQL)
schema design and implementation. Expertise in
Hadoop ecosystem (HDFS, Hive, Spark with Scala) . Hands-on experience with
Presto/Trino
and
Data Lake architectures . Practical knowledge of
stream-processing frameworks
such as
Storm and Spark Streaming . Experience with
orchestration & workflow tools : Airflow, Luigi, Automic. Proficiency with
Kubernetes
and containerized deployments. Strong understanding of
cloud services
(GCP/AWS/Azure) and
Vertex AI . Excellent problem-solving, debugging, and optimization skills. Preferred Skills (Nice to Have)
Experience with
machine learning integration
and MLOps workflows. Knowledge of
NoSQL databases
(MongoDB, Cassandra, etc.). Exposure to
observability/monitoring tools
(Grafana, Prometheus, ELK, etc.). Familiarity with
Agile/Scrum methodologies .