Job Title: Senior Data Engineer

We seek an experienced Senior Data Engineer to join our team and lead the design, development, and maintenance of scalable data pipelines and cloud-based infrastructure. You will work with data scientists, analysts, and cross-functional teams to ensure seamless data integration and performance across our platforms.

Key Responsibilities:

• Data Pipeline Development : Build and maintain reliable ETL/ELT processes using Python and SQL to efficiently extract, transform, and load data from various sources into our data platforms.
• Database Optimization : Manage and optimize SQL databases and data warehouses, ensuring efficient data retrieval and high performance.
• Data Integration : Merge structured and unstructured data from diverse sources into a unified format for analysis and decision-making.
• Data Governance : Implement data quality checks, validation protocols, and governance standards to maintain data integrity and consistency.
• Collaboration : Partner with data scientists, software engineers, and product teams to define data requirements and develop solutions that meet business needs.
• Performance Tuning : Enhance the performance of large-scale data processing systems, optimizing for faster data access and usability.
• Documentation : Maintain detailed documentation of data engineering processes, pipelines, and system architectures.
• Innovation : Stay current with emerging trends and technologies in data engineering and cloud services, integrating new tools and approaches as appropriate.

Required Qualifications:

• 6+ years of experience in advanced Python for data manipulation, automation, and scripting.
• 6+ years of experience in advanced SQL , with expertise in complex query writing and database optimization.
• Hands-on experience with Apache Airflow or Kubeflow for scheduling and workflow automation.
• Strong experience with Azure Cloud (preferred), AWS , or GCP managing data solutions and infrastructure.
• Experience with Azure Kubernetes and cloud-native data architectures.
• Familiarity with big data technologies like Spark or Hadoop and data lake architectures.
• Knowledge of CI/CD pipelines , version control (Git), and containerization tools like Docker.
• ** _ C2C Only_**

Preferred Skills:

• Experience in data governance and quality assurance.
• Familiarity with DevOps practices and collaboration within a cross-functional engineering environment.

Education:

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.