Senior Python Data Engineer Job Overview: We are seeking an experienced Senior Python Data Engineer with a strong background in building Extract, Transform, Load (ETL) processes and a deep understanding of AWS serverless cloud environments. As a key member of our data engineering team, you will play a critical role in designing, developing, and maintaining data pipelines that facilitate data ingestion, transformation, and storage for our organization. Your expertise will contribute to the foundation of our data infrastructure, enabling data-driven decision-making and analytics. Key Responsibilities: • ETL Pipeline Development: Design, develop, and maintain ETL processes using Python, AWS Glue, or other serverless technologies to ingest data from various sources (databases, APIs, files), transform it into a usable format, and load it into data warehouses or data lakes. • AWS Serverless Expertise: Leverage AWS services such as AWS Lambda, AWS Step Functions, AWS Glue, AWS S3, and AWS Redshift to build serverless data pipelines that are scalable, reliable, and cost-effective. • Data Modelling: Collaborate with data scientists and analysts to understand data requirements and design appropriate data models, ensuring data is structured optimally for analytical purposes. • Data Quality Assurance: Implement data validation and quality checks within ETL pipelines to ensure accuracy, completeness, and consistency of data. • Performance Optimization: Continuously optimize ETL processes for efficiency, performance, and scalability, monitoring and troubleshooting any bottlenecks or issues that may arise. • Documentation: Maintain comprehensive documentation of ETL processes, data lineage, and system architecture to ensure knowledge sharing and compliance with best practices. • Security and Compliance: Implement data security measures, encryption, and compliance standards (e.g., GDPR, HIPAA) as required for sensitive data handling. • Monitoring and Logging: Set up monitoring, alerting, and logging systems to proactively identify and resolve issues in data pipelines. • Collaboration: Work closely with cross-functional teams, including data scientists, data analysts, software engineers, and business stakeholders to understand data requirements and deliver solutions. • Continuous Learning: Stay current with industry trends, emerging technologies, and best practices in data engineering and cloud computing, and apply them to enhance existing processes. Senior Python Data Engineer Qualifications: • Bachelor's or Master's degree in Computer Science, Data Science, or a related field. • Proven experience as a Data Engineer, with a focus on ETL pipeline development. • Strong proficiency in Python programming. • In-depth knowledge of AWS serverless technologies and services. • Familiarity with data warehousing concepts and tools (e.g., Redshift, Snowflake). • Experience with version control systems (e.g., Git). • Strong SQL skills for data extraction and transformation. • Excellent problem-solving and troubleshooting abilities . • Ability to work independently and collaboratively in a team environment. • Effective communication skills for articulating technical concepts to nontechnical stakeholders. • Certifications such as AWS Certified Data Analytics - Specialty or AWS Certified DevOps Engineer are a plus. Preferred Experience: • Knowledge of data orchestration and workflow management tools • Familiarity with data visualization tools (e.g., Tableau, Power BI). • Previous experience in industries with strict data compliance requirements (e.g., insurance, finance) is beneficial. • Total experience 05 to 07 years and domain experience 03 to 04 years.