Lead Data Engineer: AI-Ready Data Platforms & ML Analytics

Tieto; Dallas (TX); On-site; USD 150,000 - 190,000; Full time

Job summary

Tieto is seeking a Lead Data Engineer to design, build, and deliver scalable enterprise data and AI-ready solutions. The role requires hands-on expertise in Snowflake, Nexla, Apache Airflow, SQL, and Python, plus practical GenAI-powered tooling.

You will mentor engineers and work with cross‑functional teams to support analytics, ML, LLMs, RAG, and Agentic AI initiatives while delivering with Agile methods.

Qualifications

• Bachelor's degree in a related field is required.
• Hands-on experience with Snowflake, SQL, and Python.
• Experience with Nexla or similar ETL/ELT platforms.
• Proven ability to design AI-ready data architectures and pipelines.
• Strong knowledge of data governance, security, and compliance.

Responsibilities

• Lead design, development, optimization, and support of enterprise data platforms.
• Build scalable ETL/ELT solutions using Snowflake, Nexla, SQL, and Python.
• Develop and manage Apache Airflow DAGs, workflows, and monitoring.
• Design AI-ready data architectures for ML, GenAI, and RAG.
• Use Copilot, Claude, Cursor, GitHub Copilot to boost productivity.
• Collaborate with AI/ML teams on data ingestion, governance, and model-serving.
• Implement data quality, lineage, observability, governance, security, and compliance.
• Lead code reviews, architecture discussions, and root-cause analysis.

Skills

Snowflake

Nexla

Apache Airflow

SQL

Python

AI-assisted development tools

LLMs, RAG, vector embeddings

Agentic AI

Agile & distributed teams

Data platforms for AI/ML

Education

Bachelor's degree in Computer Science, IT, Engineering, Data Science, or related field

Tools

Nexla

Azure

LangChain

LangGraph

CrewAI

AutoGen

Semantic Kernel

Job description

Tieto is seeking a Lead Data Engineer to design, build, and deliver scalable enterprise data and AI-ready solutions. The role requires hands-on expertise in Snowflake, Nexla, Apache Airflow, SQL, and Python, plus practical GenAI-powered tooling.

You will mentor engineers and work with cross‑functional teams to support analytics, ML, LLMs, RAG, and Agentic AI initiatives while delivering with Agile methods.