Data Engineer

Enterprise Data Foundation telemetry, as part of Cisco's telemetry data offerings, enables enhanced visibility of data for product adoption, up sale and cross sell across Cisco's enterprise portfolio.

You will design, develop, and implement scalable and efficient data pipelines using AWS services such as S3, EC2, ECS, and Aurora.

Key responsibilities include:

• Writing high-quality, maintainable Python code for data extraction, transformation, and loading (ETL) and Machine Learning / AI (LLM) processes.
• Developing and integrating with Web Services, Micro Services, and APIs to ingest and expose data from various internal and external sources.
• Implementing robust Data Engineering solutions, including data modeling, database design, and data warehousing.
• Optimizing data storage, retrieval, and processing for performance and cost-efficiency on AWS.
• Monitoring and troubleshooting data pipeline issues, ensuring data quality, integrity, and availability.
• Collaborating with data scientists, analysts, and software engineers to understand data requirements and deliver solutions.
• Contributing to the development and enforcement of data governance policies and standards.
• Staying up to date with emerging technologies and industry trends in Data Engineering, cloud computing, and data management.

Minimum qualifications:

• Proven experience in Data Engineering roles, with a solid portfolio of data pipeline development.
• Proficiency in Python for data manipulation, automation, and scripting.
• 7+ years of professional experience in data engineering or a similar role.
• Extensive experience in Data Warehouse platforms like Snowflake or BigQuery.
• Extensive experience with cloud platforms, particularly AWS, including services relevant to data storage, processing, and analytics.
• Solid understanding and practical experience with designing and consuming Web Services and APIs.
• Familiarity with Micro Services architecture and its implications for data integration.
• Experience with relational and NoSQL databases.
• Strong understanding of data warehousing concepts and best practices.
• Ability to work independently and as part of a collaborative team.
• Strong communication and interpersonal skills.

Preferred qualifications:

• Worked on at least one Machine Learning data pipeline.
• Worked on at least one LLM-based project.
• Usage of large language models for development.
• Understanding of Text Classification.
• Understanding of Tokenization and vectorization.
• Understanding of Statistical analysis of data.
• Excellent problem-solving and analytical skills.