Cloud Data Solutions Specialist

We are a cutting-edge data analytics firm delivering top-tier services to businesses. Our team excels at providing end-to-end data solutions, empowering clients to make informed decisions.

Our flagship product is an innovative ETL tool, and we're expanding our data visualization capabilities. We have a world-class data team that interprets complex data insights and communicates them effectively to stakeholders.

We're a fast-growing startup with old-school values, operating in the exciting space where data analytics meets ecommerce. This synergy creates a strong competitive advantage for us.

The global market faces challenges, but this also presents opportunities for companies like ours to thrive. We prioritize talent, fostering a culture of growth and learning.

We seek a seasoned Senior Python Data Engineer with substantial experience in cloud technologies. As a vital member of our data engineering team, you'll design, implement, and optimize data pipelines, ensuring seamless integration with cloud platforms.

• Design 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.
• 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.
• Collaborate with data scientists, analysts, and other stakeholders to design effective data models aligning with business requirements.
• Ensure scalability, reliability, and performance of our data infrastructure on cloud platforms.
• Optimize data processes for improved performance, scalability, and cost-effectiveness in a cloud environment.
• Monitor and troubleshoot issues, resolving them promptly and minimizing impact on data availability.
• Implement data quality checks and validation processes to ensure accuracy and completeness of data in our cloud-based data warehouse.
• Collaborate with cross-functional teams to identify and address data quality issues.
• Provide technical support to data scientists, analysts, and other teams to understand data requirements.
• Collaborate with engineering teams to integrate data engineering solutions into larger cloud-based systems.
• Create comprehensive documentation for data engineering processes, cloud architecture, and pipelines.

• Programming Languages: Proficiency in Python for data engineering tasks, scripting, and automation.
• Data Engineering Technologies: Extensive experience with distributed data processing frameworks.
• Understanding and hands-on experience with workflow management tools like Apache Airflow.
• Cloud Platforms: In-depth 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.
• ETL Processes: Proven expertise in designing and implementing Extract, Transform, Load (ETL) processes.
• SQL and Databases: Proficient in SQL with experience in working with relational databases and cloud-based database services.
• Data Modeling: Strong understanding of data modeling principles and experience in designing effective data models.
• Version Control: Familiarity with version control systems for tracking changes in code and configurations.
• Collaboration Tools: Experience using collaboration and project management tools for effective communication and project tracking.
• Containerization and Orchestration: Familiarity with containerization technologies and orchestration tools.
• Monitoring and Troubleshooting: Ability to implement monitoring solutions and troubleshoot issues in data pipelines.
• Data Quality Assurance: Experience in implementing data quality checks and validation processes.
• Agile Methodologies: Familiarity with agile development methodologies and practices.

• Strong problem-solving and critical-thinking abilities.
• Excellent communication skills, both written and verbal.
• Ability to work collaboratively in a cross-functional team environment.
• Attention to detail and commitment to delivering high-quality solutions.