Description

You will design and deliver big data pipelines for structured and unstructured data across multiple geographies. Lead data engagements on GCP Cloud covering data lakes, engineering, migration, and business intelligence. Design distributed, high-volume multi-thread batch, real-time, and event processing systems. Translate business requirements into functional and non-functional specifications including availability, scalability, performance, security, and resilience. Interface with IT and business stakeholders to define data requirements and ensure project delivery. Implement processes to validate data and monitor quality to ensure production accuracy. Mentor junior talent and contribute to the development of internal assets and accelerators. Collaborate with Pre-Sales teams on RFPs and RFIs to architect data solutions.

Responsibilities

• Lead multiple data engagements on GCP Cloud covering data lakes, data engineering, migration, and business intelligence.
• Design and develop distributed, high-volume multi-thread batch, real-time, and event processing systems.
• Translate business requirements into functional and non-functional specifications including availability, scalability, performance, security, and resilience.
• Implement processes to validate data and monitor quality to ensure production accuracy.
• Mentor junior talent and contribute to the development of internal assets and accelerators.

Required Skills

• Over 15 years of experience in technical, solutioning, and analytical roles.
• 5+ years of experience building and managing Data Lakes, Data Warehouses, and Data Integration solutions on GCP, AWS, or Azure.
• Expertise in architecting end-to-end data pipelines using Spark, PySpark, Scala, Dataflow, DataProc, or EMR.
• Deep knowledge of databases including Cloud SQL, Cloud Spanner, Big Table, RDS, Aurora, DynamoDB, Oracle, Teradata, MySQL, or DB2.
• Experience with distributed computing environments such as Hadoop and cloud-native storage like S3, Cloud Storage, or Athena.
• Proficiency with data orchestration and streaming tools like Airflow, Composer, Kafka, Pub-Sub, or Kinesis.
• Experience migrating on-premise data solutions to cloud environments.
• Understanding of cloud security features and policies across GCP, AWS, or Azure.
• Ability to compare products and tools across different cloud technology stacks.

Preferred Skills

• Experience with Machine Learning frameworks such as TensorFlow or PyTorch.
• Familiarity with BI reporting tools like Looker, Tableau, or Power BI.

Key Skills

Education

Any Graduate