Technical Architect

• Professional experience in Data Engineering using Google Big Query (GBQ) and Google Cloud Platform (GCP) data sets and building data pipelines.
• Hands on and deep experience working with Google Data Products (e.g. BigQuery, Dataflow, Dataproc, Dataprep, Cloud Composer, Airflow, DAG etc.).
• Python Programming Expert PySpark, Pandas
• Experience in Airflow (Create DAG, Configure the variables in Airflow, Scheduling)
• Big Data technologies and solutions (Spark, Hadoop, Hive, MapReduce) and multiple scripting and languages (YAML, Python).
• Experience in DBT to create the lineage in GCP. – Optional
• Worked in Dev-Sec-Ops (CICD) environment.
• Design and develop the ETL ELT framework using BigQuery, Expertise in Big Query concepts like Nested Queries, Clustering, Partitioning, etc.
• Experience in Data Integration, Data Transformation, Data Quality and Data Lineage tools.
• Should be able to automate the data load from Big Query using APIs or scripting language.
• E2E Data Engineering and Lifecycle (including non-functional requirements and operations) management.
• E2E Solution Design skills – Prototyping, Usability testing