Key Responsibilities:

• Data Architecture Design: Design and implement large-scale data architectures, including data warehouses, data lakes, and data pipelines.
  
• ETL Processes: Develop, maintain, and optimize ETL processes to ensure efficient data extraction, transformation, and loading from various sources.
  
• Data Pipeline Management: Build and manage data pipelines for real-time and batch data processing, ensuring high performance and reliability.
  
• Cloud Management : Work with cloud-based services (AWS, Azure, GCP) to deploy and manage data infrastructure.
  
• Data Quality and Security: Ensure data accuracy, integrity, and security by implementing quality control procedures and access controls.
  
• Collaboration: Collaborate with data scientists, analysts, and software engineers to deliver relevant data sets and support business intelligence initiatives.
  
• Machine Learning: Model Deployment: Assist in deploying machine learning models into production environments.
  
• Performance Optimization: Monitor data infrastructure performance and implement optimization strategies to improve efficiency and scalability.
  
• Documentation and Knowledge Sharing: Document data pipelines, processes, and best practices for knowledge sharing across the team
  

RequirementsRequired Qualifications:

• Experience: 8-10 years of experience in a data engineering role, with a focus on large-scale data systems.
  
  

Technical Skills:

• Strong proficiency in programming languages such as Python, Java, or Scala.
  
• Experience with big data technologies like Hadoop, Spark, and NoSQL databases.
  
• Knowledge of ETL tools (e.g., Apache Airflow, AWS Data Pipeline).
  
• Familiarity with cloud platforms (AWS, Azure, GCP).
  
• Understanding of data modeling, data warehousing, and data governance principles
  

Soft Skills:

• Excellent communication and collaboration skills.
  
• Ability to work in a fast-paced environment with multiple stakeholders.
  
• Strong analytical and problem-solving skills.
  

Nice to Have :

• Significant experience working with financial services data and a strong understanding of the financial services industry.
  
• Experience with data visualization tools such as Tableau or Power BI.