Lead Data Engineer

Simpalm; Dallas (TX); On-site; USD 103,000 - 126,000; Full time

Job summary

Simpalm, partnering with a US-based omnichannel Insurtech organization, is seeking a Lead Data Engineer to design and deliver enterprise-scale data platforms that support analytics and modern AI workloads, including LLMs and RAG. The role is based onsite in Dallas, TX.

You will own end-to-end delivery of platform capabilities such as ETL/ELT, orchestration, and data ingestion patterns, while collaborating with engineers and AI specialists to translate requirements into production-ready data and

Qualifications

• Bachelor’s degree in CS or related field (or equivalent experience).
• Strong Snowflake experience including SQL development and performance tuning.
• Hands-on ETL/ELT with Nexla and modern data tools.
• Experience with Apache Airflow including DAG development and monitoring.
• Proficiency in SQL and Python for enterprise-scale data engineering.
• Experience with AI dev tools such as Copilot/Claude/Cursor.
• Familiarity with GenAI concepts: LLMs, RAG, vector embeddings.
• Ability to design data architectures supporting AI, ML, analytics.

Responsibilities

• Lead analysis, design, and implementation of scalable data solutions.
• Collaborate across Product Engineers, Architects, Data Scientists, and AI Engineers.
• Design and optimize ETL/ELT pipelines using Snowflake, Nexla, SQL, and Python.
• Develop and manage Airflow DAGs for reliable data processing.
• Architect AI-ready data platforms for analytics, GenAI, and RAG.
• Use AI-assisted tools to accelerate delivery and code quality.
• Govern data ingestion, transformation, and serving for AI workloads.
• Support metadata, lineage, observability, and governance practices.

Skills

Data engineering

ETL/ELT

AI/ML

SQL

Education

Bachelor’s degree in CS or related field

Tools

Snowflake

Nexla

SQL

Python

Apache Airflow

Microsoft Copilot

Claude

Cursor

GitHub Copilot

Job description

Simpalm is partnering with a US-based omnichannel Insurtech organization to build enterprise-scale, AI-ready data platforms. As a Lead Data Engineer, you will design and deliver scalable data solutions that support analytics and modern AI workloads, including LLMs and RAG. The role is based onsite in Dallas, TX.

You will own the end-to-end delivery of platform capabilities such as ETL/ELT, orchestration, and data ingestion patterns, while collaborating closely with engineers and AI specialists to translate requirements into production-ready data and AI architectures. You will also leverage AI-assisted development tools to accelerate delivery and strengthen code quality and documentation.

Responsibilities

• Lead analysis, design, development, and implementation of scalable data solutions across the enterprise data warehouse and modern data platform.
• Partner with Product Engineers, Data Engineers, Architects, Data Scientists, and AI Engineers to translate business requirements into scalable data and AI solutions.
• Design, build, and optimize ETL/ELT pipelines using Snowflake, Nexla, SQL, and Python.
• Develop and manage Apache Airflow DAGs for reliable, observable data processing and scheduling.
• Design AI-ready data architectures for analytics, machine learning, GenAI, RAG, vector databases, and agentic AI solutions.
• Use AI-assisted development tools (including Microsoft Copilot, Claude, and Cursor) to improve delivery speed and code quality.
• Define data ingestion, transformation, governance, and serving patterns for AI model training and inference workloads.
• Support metadata management, data lineage, data observability, and governance practices for enterprise AI initiatives.
• Evaluate and recommend emerging AI technologies, frameworks, and engineering best practices.
• Manage agile sprint priorities, backlog refinement, story estimation, dependency tracking, and delivery commitments.
• Coordinate across onsite, offsite, offshore, and cross-functional teams to remove blockers and maintain momentum.
• Create and maintain technical design docs, data flow diagrams, AI solution architecture diagrams, and operational runbooks.
• Drive data quality, performance tuning, monitoring, and production support for critical pipelines and Snowflake workloads.
• Lead architecture reviews, code reviews, root-cause analysis, and problem-solving with engineering and business partners.
• Mentor team members on modern data engineering and AI-assisted development practices.
• Promote responsible AI practices across data privacy, security, governance, and ethical use of AI.

Requirements

• Bachelor’s degree in computer science, IT, engineering, data science, AI, or a related field (or equivalent experience).
• Strong hands-on Snowflake experience including SQL development, performance tuning, data modeling, stored procedures, and scalable processing patterns.
• Hands-on ETL/ELT experience with Nexla and modern data integration tools.
• Experience with Apache Airflow (or similar) including DAG development, scheduling, monitoring, and troubleshooting.
• Strong proficiency in SQL and Python for enterprise-scale data engineering.
• Practical experience with AI-powered dev tools such as Microsoft Copilot, Claude, Cursor, and GitHub Copilot (or similar).
• Working knowledge of GenAI concepts: LLMs, RAG, vector embeddings, prompt engineering, and agentic AI patterns.
• Experience designing data architectures and pipelines supporting AI, ML, analytics, and intelligent automation.
• Knowledge of data governance, security, privacy, lineage, and compliance for AI and enterprise data platforms.
• Proven ability to lead sprint execution, manage competing priorities, clarify scope, identify risks, and coordinate delivery.
• Strong collaboration across product engineering, data engineering, AI/ML, BI/analytics, QA, architecture, and business teams.
• Experience working with onsite, offsite, offshore, and distributed teams in an Agile environment.
• Strong analytical, problem-solving, communication, and troubleshooting skills.
• Self-starter with ownership, accountability, and attention to detail in a fast-paced environment.
• Demonstrated ability to learn and adopt emerging AI technologies quickly.

Technologies

• Snowflake, Nexla, SQL, Python, Apache Airflow
• Microsoft Copilot, Claude, Cursor, GitHub Copilot
• LLMs, Retrieval-Augmented Generation (RAG), vector databases, vector embeddings
• Apache Airflow DAGs

Compensation & Location

• Salary: $103,000 to $126,000 per year
• Location: Dallas, TX (onsite), in person