1. Data Pipeline Development: Design and implement data pipelines for data extraction, transformation, and loading (ETL) processes. Ensure data quality, reliability, and timeliness.
2. Data Integration: Oversee data integration efforts, ensuring seamless data flow between different systems and sources. Collaborate with data analysts, data scientists, and business stakeholders to define data integration requirements.
3. Data Modeling: Define and implement data models that support analytical and reporting needs. Optimize data structures for query performance and storage efficiency.
4. Database Management: Manage and optimize databases, both relational and NoSQL, for performance, scalability, and security.
- Experience: 5.5 to 8.5 years • Mandatory Skills: Python, Pyspark, Databricks, Azure Services(ADLS, ADF, ADB), SQL Advanced
Data Warehouse, Data Modeling, Data Strategy, Data Quality
- Valuable communication and Problem-solving skills.