Lovelytics

Data Engineer

• Utilize consulting and technical skills to be able to work in a client-facing project environment independently
• Be responsible for your own execution and sometimes lead individual work streams on client engagements as assigned and under supervision of engagement lead
• Collaborate with other team members to successfully deliver on projects
• Work effectively and directly communicate with both internal and client and/or partner teams
• Develop full ownership of your execution on client engagements
• Design and implement complex ETL/ELT pipelines with evidence of improved data processing times
• Successfully lead small data warehousing projects with measurable performance enhancements under management of an engagement lead
• Contribute to real-time data processing solutions and manage streaming data
• Implement security and compliance measures for data pipelines
• Design and implement version control and branching strategies and integrate them into CI/CD for promoting and testing in higher environments
• Hands-on experience working with SAP data at the table level
• Strong understanding of SAP data structures and relationships, beyond ETL tooling
• Ability to interpret SAP data in the context of underlying business processes

Lead Consultant, Data Engineer

Artificial Intelligence

• Deliver high-impact, client-facing engagements independently and/or lead specific workstreams under the supervision of an engagement lead and principal consultants.
• Build and optimize LLM applications, including AI Agents, RAG systems, evaluation pipelines, prompt chaining, and output refinement.
• Design, implement, and deploy GenAI pipelines using tools such as DSPy, MLFlow, LangChain, LlamaIndex, and Databricks Mosaic AI.
• Work hands-on with models like OpenAI GPT, LLaMA, Claude, and others—fine-tuning or prompt-tuning as required.
• Ingest and process unstructured and structured data for use in GenAI systems, including document parsing, chunking, vectorization, and retrieval.
• Collaborate with cross-functional teams to build custom UI and API integrations and GenAI-powered user experiences.
• Implement enterprise-grade best practices for security, compliance, evaluation, and governance in GenAI projects.
• Develop evaluation frameworks using MLFow, Mosaic AI Eval tools, and standard and custom metrics.
• Support CI/CD and DABs for AI applications and promote code and model artifacts across environments.
• Contribute to internal accelerators and reusable GenAI components as part of our growing framework library.
• Work closely with senior leadership to design architecture and delivery plans tailored to client needs.

Lead Consultant, Data Engineer

Senior Consultant, Gen AI