Data Warehouse Team Lead: Fabric, Databricks & AI Pipelines

ISN

Dallas (TX)

On-site

USD 140,000 - 180,000

Full time

3 days ago
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Job summary

ISN is seeking a Team Lead – Data Warehouse & Decision Support to guide technical direction and oversee ISN’s data warehouse, ETL environment, and data estate. The role is 25% people leadership and 75% hands-on work, with emphasis on Microsoft Fabric and SQL Server.

Based in Dallas, TX, the position requires onsite presence and relocation if not local; travel and collaboration with cross-functional teams are expected to drive reliability, performance, and cost management in cloud data

Qualifications

  • 8+ years of data engineering or data warehousing experience in a dynamic, data-rich environment.
  • 3+ years of leadership or project leadership experience.
  • Hands-on expertise with Microsoft Fabric, SQL, ETL and Python.

Responsibilities

  • Lead the day-to-day operation of the data warehouse, ETL environment, and semantic/reporting layers.
  • Design and lead the team’s adoption and deployment of Microsoft Fabric, Databricks and SQL Server.
  • Partner with data architecture, Technical Operations, data governance, security, and platform teams to ensure compliance, access controls, and cost management.
  • Write and review complex SQL and pipeline code; act as the final technical reviewer for major data model or pipeline changes
  • Evaluate opportunities to apply AI and LLMs to data engineering workflows and guide adoption.

Skills

Data warehousing
ETL/ELT pipelines
Python (PySpark)
Leadership
SQL
Databricks
Microsoft Fabric

Tools

Microsoft Fabric
SQL Server
Databricks
Delta tables
OneLake
Apache Spark

Job description

ISN is seeking a Team Lead – Data Warehouse & Decision Support to guide technical direction and oversee ISN’s data warehouse, ETL environment, and data estate. The role is 25% people leadership and 75% hands-on work, with emphasis on Microsoft Fabric and SQL Server.

Based in Dallas, TX, the position requires onsite presence and relocation if not local; travel and collaboration with cross-functional teams are expected to drive reliability, performance, and cost management in cloud data

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