Lead / Senior GCP Data engineer

Overview

About Tredence:
Tredence is a global data science solutions provider founded in 2013 by Shub Bhowmick, Sumit Mehra, and Shashank Dubey focused on solving the last-mile problem in AI. Headquartered in San Jose, California, the company embraces a vertical-first approach and an outcome-driven mindset to help clients win and accelerate value realization from their analytics investments. The aim is to bridge the gap between insight delivery and value realization by providing customers with a differentiated approach to data and analytics through tailor-made solutions. 

We’re focused on bridging the gap between insights delivery and value realization, partnering with our clients to help them cross the last mile gap in analytics. This DNA pushes our ecosystem to go beyond possible, helping our clients re-think their limitations and overcome their norms of ‘possible’.

Role – GCP Staff Data Engineer
Experience: 8  + years
Preferred - Data Engineering Background
Location –Bangalore, Chennai, Hyderabad, Kolkata, Pune, Gurgaon

Job Requirement:

• Have Implemented and Architected solutions on Google Cloud Platform using the components of GCP


• Experience with Apache Beam/Google Dataflow/Apache Spark in creating end to end data pipelines.


• Experience in some of the following: Python, Hadoop, Spark, SQL, Big Query, Big Table Cloud Storage, Datastore, Spanner, Cloud SQL, Machine Learning.


• Experience programming in Java, Python, etc.


• Expertise in at least two of these technologies: Relational Databases, Analytical Databases, NoSQL databases.


• Certified in Google Professional Data Engineer/ Solution Architect is a major Advantage

Skills Required:

• 8+ years’ experience in IT or professional services experience in IT delivery or large-scale IT analytics projects


• Candidates must have expertise knowledge of Google Cloud Platform; the other cloud platforms are nice to have.


• Expert knowledge in SQL development.


• Expertise in building data integration and preparation tools using cloud technologies (like Snaplogic, Google Dataflow, Cloud Dataprep, Python, etc).


• Experience with Apache Beam/Google Dataflow/Apache Spark in creating end to end data pipelines.


• Experience in some of the following: Python, Hadoop, Spark, SQL, Big Query, Big Table Cloud Storage, Datastore, Spanner, Cloud SQL, Machine Learning.


• Experience programming in Java, Python, etc.


• Identify downstream implications of data loads/migration (e.g., data quality, regulatory, etc.)


• Implement data pipelines to automate the ingestion, transformation, and augmentation of data sources, and provide best practices for pipeline operations.


• Capability to work in a rapidly changing business environment and to enable simplified user access to massive data by building scalable data solutions


• Advanced SQL writing and experience in data mining (SQL, ETL, data warehouse, etc.) and using databases in a business environment with complex datasets.