Description

You will design and deliver big data pipelines and cloud data solutions for structured and unstructured data across multiple geographies.

This role is hybrid.

Responsibilities

• Lead multiple 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, and security.
• Interface with IT and business stakeholders to define data requirements and ensure successful project delivery.
• Implement processes to validate data and monitor quality to ensure production accuracy.

Required Skills

• 15+ years of experience in technical, solutioning, and analytical roles.
• 5+ years building and managing Data Lakes, Data Warehouses, and Data Integration solutions on GCP, AWS, or Azure.
• Expertise in distributed computing environments including Hadoop and major Cloud platforms.
• Proficiency with Spark, PySpark, or Scala for data integration and ETL.
• Experience architecting scalable data warehouse solutions on BigQuery or Redshift.
• Deep knowledge of databases including Cloud SQL, Cloud Spanner, BigTable, RDS, Aurora, DynamoDB, Oracle, Teradata, MySQL, DB2, or SQL Server.
• Experience with data pipeline tools such as S3, Cloud Storage, Athena, Glue, Sqoop, Hive, Kafka, Pub-Sub, Kinesis, Dataflow, DataProc, Airflow, or Composer.
• Understanding of Cloud solutions for IaaS, PaaS, SaaS, Containers, and Microservices architecture.

Preferred Skills

• Experience with Machine Learning frameworks like TensorFlow or PyTorch.
• Familiarity with BI reporting and dashboarding tools such as Looker, Tableau, Power BI, SAP BO, Cognos, or Superset.

Key Skills

Education

Any Graduate