Python Data Engineer

Python Data Engineer:

• Designing and building optimized data pipelines using cutting-edge technologies in a cloud environment to drive analytical insights.
• Constructing infrastructure for efficient ETL processes from various sources and storage systems.
• Collaborating closely with Product Managers and Business Managers to design technical solutions aligned with business requirements.
• Leading the implementation of algorithms and prototypes to transform raw data into useful information.
• Architecting, designing, and maintaining database pipeline architectures, ensuring readiness for AI/ML transformations.
• Creating innovative data validation methods and data analysis tools.
• Ensuring compliance with data governance and security policies.
• Interpreting data trends and patterns to establish operational alerts.
• Developing analytical tools, programs, and reporting mechanisms.
• Conducting complex data analysis and presenting results effectively.
• Preparing data for prescriptive and predictive modeling.
• Continuously exploring opportunities to enhance data quality and reliability.
• Applying strong programming and problem-solving skills to develop scalable solutions.
• Passion for testing strategy, problem-solving, and continuous learning.
• Willingness to acquire new skills and knowledge.
• Possess a product/engineering mindset to drive impactful data solutions.
• Experience working in distributed environments with global teams.

Technical Skills and Experience requirements:

• Minimum 8+ years of hands-on experience designing, building, deploying, testing, maintaining, monitoring, and owning scalable, resilient, and distributed data pipelines.
• High proficiency in Python, Scala and Spark for applied large-scale data processing.
• Expertise with big data technologies, including Spark, Data Lake, Delta Lake, and Hive.
• Solid understanding of batch and streaming data processing techniques.
• Proficient knowledge of the Data Lifecycle Management process, including data collection, access, use, storage, transfer, and deletion.
• Expert-level ability to write complex, optimized SQL queries across extensive data volumes.
• Experience with RDBMS and OLAP databases like MySQL, Snowflake.
• Familiarity with Agile methodologies.
• Obsession for service observability, instrumentation, monitoring, and alerting.
• Knowledge or experience in architectural best practices for building data lakes.

Qualification

Relevant Development Experience

Relevant Experience

Overall IT Experience