Senior Engineering Lead Analyst-5

Realign Llc; Dallas (TX); On-site; USD 180,000 - 240,000; Full time

Job summary

Realign Llc is seeking an experienced Senior Engineering Lead Analyst to drive enterprise data platform modernization from on-prem to cloud, focusing on data lake, lakehouse, and AI-enabled data value chains.

You will architect scalable solutions on AWS/Azure, design data governance and metadata frameworks, and lead GenAI-enabled data products with LLMs, vectors, and memory management. Onsite roles span Los Angeles, Dallas, and Chicago with senior stakeholder exposure.

Qualifications

• Architect enterprise data platforms for data lake, Lakehouse, streaming systems.
• Design data integration and data pipeline patterns.
• Should be able to evaluate new technologies and run proof of concepts.
• Should be able to set data and AI strategy for data organization.
• Established data Quality, lineage and metadata standards.
• Drives adoption of responsible AI frameworks.
• Create architectural guardrails.
• Lead adoption of data contracts, lineage across data organizations.
• Reviews design and elevate architectural thinking across teams.

Responsibilities

• Lead enterprise data platform modernization from on-prem to cloud for banking and insurance clients.
• Architect and implement scalable solutions using Snowflake and Databricks on AWS and Azure.
• Design and implement AI and Gen AI solution for data value chain.
• Design data integration pipelines (batch, real-time, big data) and analytics platforms.
• Define and implement data governance, quality, metadata, and lineage frameworks with GenAI capabilities.
• Act as a trusted advisor to senior business and IT stakeholders.
• Architect Agentic AI ecosystems using LLMs, vector databases, and orchestration frameworks.
• Define MCPs to chain reasoning, retrieval, and action models.
• Design A2A communication protocols for multi-agent workflows.
• Implement retrieval-augmented generation (RAG) pipelines with memory and tool usage.

Skills

Data architecture

Data governance

MLOps

Python

LLMs

Cloud platforms

Snowflake/Databricks

Tools

LangChain

Vector DBs

FAISS

Pinecone

Weaviate

Databricks

Snowflake

Job description

Job Title: Senior Engineering Lead Analyst
Location: Los Angeles, CA / Dallas, TX / Chicago, IL (Onsite)Fulltime

Job Description

Must Have Technical/Functional Skills

• Architect enterprise data platforms for data lake, Lakehouse, streaming systems.
• Design data integration and data pipeline patterns
• Should be able to evaluate new technologies and run proof of concepts.
• Should be able to set data and AI strategy for data organization.
• Established data Quality, lineage and metadata standards
• Ensured compliance with privacy, security and regulation
• Drives adoption of responsible AI frameworks
• Created architectural guardrails
• Drive consensus on standards (eg data contracts, lineage) across different data organizations
• Reviews design and elevate architectural thinking across teams
• Creates reusable patterns, templates and reference architectures
• Very strong understanding and experience on Data products, data mesh and Medallion Architecture implementation
• Design and implement AI and Gen AI solution for data value chain
• Strong experience with LLMs, prompt engineering, and agent frameworks (LangChain, AutoGen, CrewAI).
• Deep understanding of MCPs, ReAct, Tree of Thought, and AutoGPT-style reasoning.
• Hands-on with Python, OpenAI APIs, Anthropic Claude, Vector DBs (FAISS, Pinecone, Weaviate).
• Experience with A2A orchestration, agent memory strategies, and tool calling.
• Strong grasp of enterprise architecture, data governance, and security protocols.
• Experience with cloud platforms (Azure, AWS, GCP) and MLOps pipelines.
• Very strong understanding and experience on Data products, data mesh and Medallion Architecture implementation
• Implement retrieval-augmented generation (RAG) pipelines with memory, context management, and tool usage.
• Define Model Context Protocol (MCPs) to chain reasoning, retrieval, and action models.
• Hands-on with Python, OpenAI APIs, Anthropic Claude, Vector DBs (FAISS, Pinecone, Weaviate).
• Lead enterprise data platform modernization from on-prem to cloud for banking and insurance clients.
• Architect and implement scalable solutions using Snowflake and Databricks on AWS and Azure
• Design and implement AI and Gen AI solution for data value chain
• Design data integration pipelines (batch, real-time, big data) and analytics platforms
• Define and implement data governance, quality, meta data, and lineage frameworks and should be able to leverage GenAI capabilities.
• Act as a trusted advisor to senior business and IT stakeholders
• Architect Agentic AI ecosystems using LLMs, vector databases, and orchestration frameworks (LangChain, AutoGen, CrewAI).
• Define Model Context Protocol (MCPs) to chain reasoning, retrieval, and action models.
• Design Agent-to-Agent (A2A) communication protocols for collaborative multi-agent workflows.
• Implement retrieval-augmented generation (RAG) pipelines with memory, context management, and tool usage.

Generic Managerial Skills, If any

• 15–20 years of experience in data architecture, data engineering, and analytics platforms
• Strong consulting experience in large BFSI transformation programs
• Hands-on expertise with Snowflake and Databricks (Lakehouse architecture)
• Design and implement AI and Gen AI solution for data value chain
• Very strong understanding and experience on Data products, data mesh and Medallion Architecture implementation
• Experience with cloud data services in aws,azure,gcp
• Strong background in data integration, reporting, and big data ecosystems
• Experience working in regulated environments with data governance and compliance requirements
• Excellent stakeholder communication and leadership skills

Roles & Responsibilities

• Lead enterprise data platform modernization from on-prem to cloud for banking and insurance clients.
• Architect and implement scalable solutions using Snowflake and Databricks on AWS and Azure
• Design and implement AI and Gen AI solution for data value chain
• Design data integration pipelines (batch, real-time, big data) and analytics platforms
• Define and implement data governance, quality, meta data, and lineage frameworks and should be able to leverage GenAI capabilities.
• Act as a trusted advisor to senior business and IT stakeholders
• Architect Agentic AI ecosystems using LLMs, vector databases, and orchestration frameworks (LangChain, AutoGen, CrewAI).
• Define Model Context Protocol (MCPs) to chain reasoning, retrieval, and action models.
• Design Agent-to-Agent (A2A) communication protocols for collaborative multi-agent workflows.
• Implement retrieval-augmented generation (RAG) pipelines with memory, context management, and tool usage.

Generic Managerial Skills, If any

• 15–20 years of experience in data architecture, data engineering, and analytics platforms
• Strong consulting experience in large BFSI transformation programs
• Hands-on expertise with Snowflake and Databricks (Lakehouse architecture)
• Design and implement AI and Gen AI solution for data value chain
• Very strong understanding and experience on Data products, data mesh and Medallion Architecture implementation
• Experience with cloud data services in aws,azure,gcp
• Strong background in data integration, reporting, and big data ecosystems
• Experience working in regulated environments with data governance and compliance requirements
• Excellent stakeholder communication and leadership skills