Job description
Role - GCP Data Engineer (Visualization experience)
As a Data Engineer you will work on process of transforming raw data to a usable format, which is then further analyzed by other teams. Cleansing, organizing, and manipulating data using pipelines are some of the key responsibilities of a data engineer. You will also work on applying data engineering principles on the Google Cloud Platform to optimize its services. And create interactive dashboards/reports to present it to the stakeholders.
Role and Responsibilities:
Create and maintain optimal data pipeline architecture,
Assemble large, complex data sets that meet functional / non-functional business requirements.
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and other data sources
Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
Design intuitive and visually appearing visualizations to communicate complex data insights to users using Tableau, Streamlit, Dash Enterprise and Power BI
Use Flask to develop APIs that integrate data from various sources and facilitate automation of business processes.
Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
Candidate Profile:
Required Qualification and Skills:
Expert in DASH Enterprise in developing friendly UI and strong story telling experience.
Ability to conduct real-time data exploration, predictive modeling integration and a seamless deployment of machine learning modules to GCP.
Overall, 5-8 years of experience on ETL technologies
3+ years of experience in data engineering technologies like SQL, Hadoop, Big Query, Dataproc, Composer
Strong Python/Pyspark Data Engineer Skills
Hands-on experience with data visualizations like Tableau, Power BI, Dash and Streamlit
Experience in building interactive dashboards, visualizations, and custom reports for business users.
Knowledge of Flask for developing APIs and automating data workflows
Experience in data automation and implemented workflows in a cloud environment.
Strong SQL ETL skills
GCP data engineer certified to be preferred.
Ability to understand and design the underlying data/schema
Strong communication skills to effectively communicate client updates.
Originally posted on Himalayas
Who can apply
Eligible countries: United States. Accepted UTC offsets: UTC-10, UTC-9, UTC-8, UTC-7, UTC-6, UTC-5, UTC+14. Review the full description for employer-specific work authorization, residency and schedule requirements.