
Big Data Engineer and Architect
7 days ago
Data Pilot is committed to helping organizations unlock the full potential of their data assets and maximize business value through our expert engineering and business acumen. As an Associate Data Architect, you will play a crucial role in designing and implementing scalable, efficient data architectures that support advanced data engineering and analytics projects.
Our dynamic team works closely with clients to understand their unique business challenges and develop tailored solutions that meet their specific needs. With a strong focus on collaboration and innovation, we strive to deliver exceptional results that drive business growth and success.
Key Responsibilities:
- Develop end-to-end data architectures for various data engineering and analytics projects, incorporating principles of medallion and lakehouse models to support real-time and batch analytics.
- Use ETL tools, Python scripting, and SQL to construct scalable data pipelines that extract data from disparate sources, transform it to meet business needs, and load it into a centralized data warehouse, ensuring data quality and accessibility.
- Leverage cloud computing platforms (AWS, GCP, Azure) to build secure, efficient, and scalable data infrastructures that support complex data analysis and reporting.
- Apply in-depth knowledge of data warehouse concepts to design and optimize data storage solutions that support advanced data analytics and reporting.
- Collaborate with the data science team to facilitate the development and deployment of machine learning models, providing technical expertise to guide project approaches and outcomes.
Qualifications:
- Minimum Bachelor's degree in computer science or a related field.
- 4-5 years of experience in data engineering, analytics, and data science, with a significant focus on data architecture and pipeline development.
- 2-3 years of hands-on experience with at least two major cloud platforms (AWS, GCP, Azure) and a solution architect certification in one of these platforms.
- Deep understanding of data warehouse concepts and experience in designing data warehousing solutions.
- Proficiency in ETL tools, Python scripting, and SQL.
- Knowledge of Spark and Databricks is highly desirable.
- Experience in building and deploying machine learning models is highly desirable.
- Strong analytical and problem-solving skills and the ability to work collaboratively with cross-functional teams.
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