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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 scaling Retrieval-Augmented Generation (RAG) pipelines, optimizing data pipelines, and maintaining vector databases. Proficient in data mining, ETL processes, and ensuring data quality while effectively communicating technical requirements to diverse stakeholders.
Highest-signal resume keywords
Data Pipeline DevelopmentVector Database ManagementETL ProcessesData Quality AssuranceCloud Platform Certification
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 MiningData StorageExtract-Transform-Load (ETL)Data Pipeline DevelopmentData ModellingRelational DatabasesNoSQL DatabasesVector EmbeddingsKnowledge GraphsCI/CD Pipelines
Soft Skills
Problem-SolvingAnalytical SkillsCritical ThinkingAttention to DetailCommunication Skills
Tools & Technologies
PineconeMilvusWeaviateGlueDatabricksSynapseDataprocPostgreSQLDB2MongoDB
Certifications & Qualifications
Open Certified Technical Specialist with Data Engineering SpecializationAWS Certified Data Analytics – SpecialtyElastic Certified EngineerGoogle Cloud Professional Data EngineerMicrosoft Certified: Azure Data Engineer Associate
Industry Keywords
Cloud ModernizationData InfrastructureAutomated Data GuardrailsSemantic LayersSocial Coding
Tech Stack
Tools & technologiesAWSAzureCloudETLMongoDBNoSQLPostgres
About the role
Key responsibilities & impact- Design and scale Retrieval-Augmented Generation (RAG) pipelines
- Transform unstructured IT logs and documentation into optimized vector embeddings
- Maintain the health and performance of vector databases such as Pinecone, Milvus, or Weaviate
- Build knowledge graphs and semantic layers
- Create automated data guardrails to detect noise, bias, and personally identifiable information before it reaches models
- Identify and resolve data quality issues at the source
- Build, deploy, and maintain CI/CD pipelines for data infrastructure
- Ensure data context remains fresh and reliable
Requirements
What you’ll need- Expertise in data mining, data storage and Extract-Transform-Load (ETL) processes
- Experience in data pipeline development and tooling, e.g., Glue, Databricks, Synapse, or Dataproc
- Experience with relational and NoSQL databases, including PostgreSQL, DB2, and MongoDB
- Excellent problem-solving, analytical, and critical thinking skills
- Ability to manage multiple projects simultaneously while maintaining attention to detail
- Ability to communicate with technical and non-technical colleagues and translate business needs into technical requirements
- Preferred: experience as a Data Engineer and/or in cloud modernization
- Preferred: experience in data modelling
- Preferred: professional certification, e.g. Open Certified Technical Specialist with Data Engineering Specialization
- Preferred: cloud platform certification, e.g. AWS Certified Data Analytics – Specialty, Elastic Certified Engineer, Google Cloud Professional Data Engineer, or Microsoft Certified: Azure Data Engineer Associate
- Preferred: understanding of social coding and IDEs, e.g. GitHub and Visual Studio
- Preferred: degree in a scientific discipline such as Computer Science, Software Engineering, or Information Technology
Benefits
Comp & perks- Flexible, supportive environment
- Well-being prioritized
- Hybrid-friendly culture
- Be Well programs supporting financial, mental, physical, and social health
- Personalized development goals
- Continuous feedback
- Certifications with Microsoft, Google, and Amazon
- Coaching and hands-on learning experiences
- Cutting-edge learning opportunities
- Career path and development tools