Senior Data Engineering Specialist

About us:

We are an ecommerce focused end-to-end data analytics firm assisting enterprises & brands in data-driven decision making to maximize business value. Our suite of work spans extraction, transformation, visualization & analysis of data delivered via industry-leading products, solutions & services. Our flagship product is a cloud-based ETL tool. We have now ventured into building exciting ease-of-use data visualization solutions on top of it. And lastly, we have a world-class data team which understands the story the numbers are telling and articulates the same to CXOs thereby creating value.

Where we are Today:

We are a boot-strapped, profitable & fast-growing (2x y-o-y) startup with old-school value systems. We play in a very exciting space which is intersection of data analytics & ecommerce both of which are game-changers. Today, the global economy faces headwinds forcing companies to downsize, outsource & offshore creating strong tailwinds for us. We are an employee-first company valuing talent & encouraging talent and live by those values at all stages of our work without compromising on the value we create for our customers. We strive to make a career and not just a job for talented folks who have chosen to work with us.

The Role:

We are seeking a seasoned and proficient Senior Python Data Engineer with substantial experience in cloud technologies. As a pivotal member of our data engineering team, you will play a crucial 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.

Responsibilities:

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 seamlessly 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.

Technical Skills: