Skills required: Must have experience with: Big Data infrastructure design using Cloud VMs and VPCs, Cloud GPUs, Cloud load balancer, Cloud DNS and CDN, and Serverless; Design and develop Orchestration pipelines using Apache Airflow, Automic, Crontab, Control-M, Google Cloud composer and Azure Data factory (ADF); Design MLOps pipelines using Vertex AI platform, Google AutoML, MLFlow, Dialogflow, Gemini Code Assist, BigQuery ML & Azure Databricks; Design and develop data ingestion batch and streaming pipelines using Spark Connect, Sqoop, Google Cloud Pub/Sub, Google Cloud Dataflow, Apache NiFi, Azure Data Factory, Azure Event hubs, Azure DataBricks and Azure Stream analytics; Design pipelines for processing streaming data using Apache Kafka core, Confluent Kafka connect, Confluent KsqlDB, Apache Spark Streaming, Apache Spark Structured Streaming, Google Cloud functions, Google Data Stream, Google Dataproc and Apache Flink; Develop Data models using ER(Erwin) Studio and Microsoft Visio; Perform SQL operations using Hive, Presto (Trino), Apache Drill, Spark SQL, Hudi with Spark & hive, and Apache Iceberg with Spark; Build ETL Pipelines using Apache Spark, Scala, PySpark, Azure-databricks and Google-databricks; Design and develop Cloud Data Warehousing platforms using Google BigQuery, Google BigLake, Azure Synapse, Azure Data Lake, Snowflake, Apache Hudi and Databricks; Build dashboards and reports using Looker, Looker Studio, Tableau, PowerBI, Plotly, Ggplot2, & Uber H3; Perform data crunching/mining using Tableau Prep, Alteryx, DBT, Dataiku, RapidMiner, KNIME and Weka. Minimum education and experience required: Master's degree or the equivalent in Computer Science, Information Technology, Engineering, or a related field; OR Bachelor's degree or the equivalent in Computer Science, Information Technology, Engineering, or a related field plus 2 years of experience in software engineering or related experience.