ETL Specialist - GCP

You should have a minimum of 5 years of IT experience with a good understanding of analytics tools for effective data analysis. You must have prior experience working in production deployment and production support teams. It is essential to have hands-on experience with Big Data tools such as Hadoop, Spark, Apache Beam, and Kafka. Proficiency in object-oriented/object function scripting languages like Python, Java, C++, Scala, etc., is required. Additionally, experience with any Data Warehousing tools like BQ, Redshift, Synapse, or Snowflake is preferred. You should possess expertise in ETL processes and Data Warehousing concepts. A strong understanding and experience with both relational and non-relational databases like MySQL, MS SQL Server, Postgres, MongoDB, and Cassandra are necessary. Experience working with cloud platforms like GCP and workflow management tools such as Apache Airflow is a plus. Preferred qualifications include knowledge of design best practices for OLTP and OLAP Systems, participation in database and pipeline design, exposure to load testing methodologies, debugging pipelines, and handling delta loads, as well as experience in heterogeneous migration projects. As part of your roles and responsibilities, you will be responsible for developing high-performance and scalable solutions using GCP for extracting, transforming, and loading big data. You will design and build production-grade data solutions from data ingestion to consumption using Java/Python. Additionally, you will design and optimize data models on GCP cloud utilizing GCP data stores like BigQuery, handle deployment processes efficiently, and optimize data pipelines for performance and cost in large-scale data lakes. Your tasks will also include writing complex and optimized queries across large datasets, creating data processing layers, collaborating closely with Data Engineers to identify the right tools for delivering product features through POC, and interacting with business stakeholders, BAs, and other Data/ML engineers as a collaborative team player. Moreover, you will be expected to research new use cases for existing data.,