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Senior Cloud Data Architect
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About us:
We are an ecommerce focused end to end data analytics firm assisting enterprises & brands in data driven decision making. Our suite of work spans extraction, transformation, visualization and analysis of data delivered via industry leading products, solutions and services.
Our flagship product is a data processing tool used by multiple clients for ETL operations. We have now ventured into building exciting ease of use data visualization solutions on top of our data processing tool.
Where we are Today:
We are a fast growing startup with old school value systems. We play in a very exciting space which is intersection of data analytics and ecommerce both of which are game changers. The global economy faces headwinds forcing companies to downsize outsource offshore creating strong tail winds for us.
We are an employee first company valuing talent encouraging talent and live by those values at all stages of our work without comprising on the value we create for our customers.
The Role:
We are seeking a seasoned and proficient senior 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.
Responsibilities:
- Data Pipeline Development
- Design develop and maintain scalable 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.
Required Skills and Qualifications
Technical Skills:
- Proficiency in Python for data engineering tasks scripting and automation.
- Extensive experience with data engineering frameworks like distributed data processing.
- Understanding and hands-on experience with workflow management tools like Apache Airflow.
- Knowledge and hands-on experience with at least one major cloud platform: AWS Azure or Google Cloud. Familiarity with cloud-native services for data processing storage and analytics.
- Experience in implementing SQL queries and working with relational databases e.g PostgreSQL MySQL.
- Strong understanding of data modeling principles and experience in designing effective data models.
- Familiarity with version control systems e.g Git for tracking changes in code and configurations.
- Ability to implement monitoring solutions and troubleshoot issues in data pipelines.
- Experience in implementing data quality checks and validation processes.
Benefits
As a key member of our team you will have the opportunity to grow learn and contribute to cutting edge projects. If you possess the required technical skills and are passionate about leveraging cloud technologies for data engineering we encourage you to apply. Please submit your resume and a cover letter highlighting your technical expertise and relevant experience.
