Sr Data Engineer

• Design, develop, and maintain data solutions for data generation, collection, and processing
• Be a key team member that assists in design and development of the data pipeline
• Create data pipelines and ensure data quality by implementing ETL processes to migrate and deploy data across systems
• Contribute to the design, development, and implementation of data pipelines, ETL/ELT processes, and data integration solutions
• Develop and maintain data models, data dictionaries, and other documentation to ensure data accuracy and consistency
• Implement data security and privacy measures to protect sensitive data
• Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions
• Collaborate and communicate effectively with product teams
• Collaborate with Data Architects, Business SMEs, and Data Scientists to design and develop end-to-end data pipelines to meet fast paced business needs across geographic regions
• Identify and resolve complex data-related challenges
• Adhere to best practices for coding, testing, and designing reusable code/component
• Explore new tools and technologies that will help to improve ETL platform performance
• Participate in sprint planning meetings and provide estimations on technical implementation

• Doctorate degree / Master's degree / Bachelor's degree and 8 to 13 years of Computer Science, IT or related field experience
• Hands on experience with big data technologies and platforms, such as Databricks, Apache Spark (PySpark, SparkSQL),Snowflake, workflow orchestration, performance tuning on big data processing
• Experienced with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven etc.), automated unit testing, and Dev Ops
• Proficient in SQL, Python for extracting, transforming, and analyzing complex datasets from relational data stores
• Proficient in Python with strong experience in ETL tools such as Apache Spark and various data processing packages, supporting scalable data workflows and machine learning pipeline development.
• Strong understanding of data modeling, data warehousing, and data integration concepts
• Proven ability to optimize query performance on big data platforms
• Knowledge on Data visualization and analytics tools like Spotfire, PowerBI

• Experience with Software engineering best-practices, including but not limited to version control, infrastructure-as-code, CI/CD, and automated testing
• Knowledge of Python/R, Databricks, SageMaker, cloud data platforms
• Strong knowledge on Oracle / SQL Server, Stored Procedure, PL/SQL,
• Knowledge on LINUX OS
• Experience in implementing Retrieval-Augmented Generation (RAG) pipelines, integrating retrieval mechanisms with language models.
• Skilled in developing machine learning models using Python, with hands-on experience in deep learning frameworks including PyTorch and TensorFlow.
• Strong understanding of data governance frameworks, tools, and best practices.
• Knowledge of vector databases, including implementation and optimization.
• Knowledge of data protection regulations and compliance requirements (e.g., GDPR, CCPA)
• Databricks Certificate preferred
• AWS Data Engineer/Architect
• Excellent critical-thinking and problem-solving skills
• Strong communication and collaboration skills
• Demonstrated awareness of how to function in a team setting
• Demonstrated presentation skills

Competitive and comprehensive Total Rewards Plans that are aligned with local industry standards