Senior Cloud Data Engineer

14 hours ago

Anantapur, Andhra Pradesh, India beBeeData Full time US$ 60,000 - US$ 1,00,000
About Analytics Solutions

We are a leading-edge data analytics firm that helps enterprises and brands make informed decisions to drive business growth. Our suite of services spans extraction, transformation, visualization, and analysis of data delivered via cutting-edge products and solutions.

We have developed an ETL tool called Daton and now offer exciting ease-of-use data visualization solutions on top of it. Additionally, we have a world-class data team that understands the story behind the numbers and communicates this effectively to CXOs.

Company Overview

We are a profitable and fast-growing startup with old-school values. We operate in a rapidly evolving space where data analytics and ecommerce intersect, creating strong tailwinds for our success.

The current economic climate presents challenges that force companies to downsize, outsource, or offshore, creating opportunities for us to thrive. We prioritize talent and live by core values at every stage of our work, ensuring we deliver exceptional value to our customers.

We strive to create a long-term career path for talented professionals who choose to work with us.

The Role

We seek an experienced Senior Python Data Engineer with substantial expertise in cloud technologies. As a key member of our data engineering team, you will play a vital role in designing, implementing, and optimizing data pipelines, ensuring seamless integration with cloud platforms.

The ideal candidate will possess a strong command of Python, data engineering principles, and a proven track record of successful implementation of scalable solutions in cloud environments.

Data Pipeline Development

Design, develop, and maintain scalable and efficient data pipelines using Python and cloud-based technologies.

Implement Extract, Transform, Load (ETL) processes to move data from diverse sources into our cloud-based data warehouse.

Cloud Integration

Utilize cloud platforms (e.g., Google Cloud, AWS, Azure) to deploy, manage, and optimize data engineering solutions.

Leverage cloud-native services for storage, processing, and analysis of large datasets.

Data Modelling and Architecture

Collaborate with data scientists, analysts, and other stakeholders to design effective data models that align with business requirements.

Ensure the scalability, reliability, and performance of the overall data infrastructure on cloud platforms.

Optimization and Performance

Continuously optimize data processes for improved performance, scalability, and cost-effectiveness in a cloud environment.

Monitor and troubleshoot issues, ensuring timely resolution and minimal impact on data availability.

Quality Assurance

Implement data quality checks and validation processes to ensure the accuracy and completeness of data in the cloud-based data warehouse.

Collaborate with cross-functional teams to identify and address data quality issues.

Collaboration and Communication

Work closely with data scientists, analysts, and other teams to understand data requirements and provide technical support.

Collaborate with other engineering teams to seamlessly integrate data engineering solutions into larger cloud-based systems.

Documentation

Create and maintain comprehensive documentation for data engineering processes, cloud architecture, and pipelines.

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