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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and implementing scalable data pipelines using AWS services, proficient in Python for ETL processes, and experienced in data warehousing and cloud computing. Collaborates effectively with cross-functional teams to ensure data quality and governance.
Highest-signal resume keywords
Data Pipeline DevelopmentAWS Services (S3, EC2, ECS, Aurora)Python ProgrammingData Warehousing (Snowflake, BigQuery)Web Services and APIs
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data EngineeringETL ProcessesData ModelingDatabase DesignData WarehousingRelational DatabasesNoSQL DatabasesMachine LearningLarge Language ModelsStatistical Analysis
Soft Skills
Strong CommunicationInterpersonal SkillsProblem-SolvingAnalytical SkillsCollaboration
Tools & Technologies
AWSSnowflakeBigQueryMicro ServicesData Governance
Industry Keywords
Data ManagementCloud ComputingData QualityData IntegrityData Availability
Tech Stack
Tools & technologiesAWSBigQueryCloudEC2ETLNoSQLPythonSnowflake
About the role
Key responsibilities & impact- Design, develop, and implement scalable and efficient data pipelines using AWS services such as S3, EC2, ECS, and Aurora
- Write maintainable Python code for data extraction, transformation, loading (ETL), and Machine Learning/AI (LLM) processes
- Develop and integrate Web Services, Micro Services, and APIs to ingest and expose data from internal and external sources
- Implement data engineering solutions including data modeling, database design, and data warehousing
- Optimize data storage, retrieval, and processing for performance and cost-efficiency on AWS
- Monitor and troubleshoot data pipeline issues, ensuring data quality, integrity, and availability
- Collaborate with data scientists, analysts, and software engineers to understand data requirements and deliver solutions
- Contribute to data governance policies and standards
- Stay current with emerging technologies and industry trends in data engineering, cloud computing, and data management
Requirements
What you’ll need- 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 with data warehouse platforms such as 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: worked on at least one Machine Learning data pipeline
- Preferred: worked on at least one LLM-based project
- Preferred: usage of large language models for development
- Preferred: understanding of text classification
- Preferred: understanding of tokenization and vectorization
- Preferred: understanding of statistical analysis of data
- Preferred: excellent problem-solving and analytical skills
Benefits
Comp & perks- Opportunities to grow and build solutions at global scale
- Collaborative team environment
- Cisco's technology-driven work with security, visibility, and insights across digital footprints