Azure Data Engineer Lead (Databricks & Lakehouse)

Lenora Systems Inc; Greenfield (IN); On-site; USD 140,000 - 190,000; Full time

Job summary

Lenora Systems Inc is seeking an experienced Data Engineering Tech Lead to drive scalable Lakehouse solutions on Azure, including Databricks, PySpark, ADF, and ADLS Gen2. You will guide architecture, optimize batch and streaming pipelines, and ensure governance and security across data platforms.

You will mentor engineers, collaborate with product and analytics teams, and define reusable workflows for efficient data delivery. Strong Azure expertise and leadership are essential.

Qualifications

• 4+ years experience in Azure Databricks with PySpark.
• 2+ years experience in Databricks workflow & Unity catalog.
• 3+ years experience in ADF (Azure Data Factory).
• 3+ years experience in ADLS Gen 2.
• 3+ years experience in Azure SQL.
• 5+ years experience in Azure Cloud platform.
• 2+ years experience in Python programming & packaging.

Responsibilities

• Lead design, development, optimization, and maintenance of scalable data engineering and Lakehouse solutions.
• Oversee batch and near-real-time data processing pipelines across enterprise sources.
• Ensure data governance, security, and quality across the Lakehouse.
• Mentor junior engineers and drive technical leadership and code quality.
• Collaborate with stakeholders to translate requirements into analytics data models.
• Define modular, reusable workflows using Azure Data Factory and Databricks Workflows.

Skills

Azure Databricks

PySpark

Azure Data Factory

ADLS Gen2

Azure SQL

Azure Cloud

Python

Unity Catalog

Databricks Workflows

Tools

Databricks Workflows

Unity Catalog

Job description

Lenora Systems Inc is seeking an experienced Data Engineering Tech Lead to drive scalable Lakehouse solutions on Azure, including Databricks, PySpark, ADF, and ADLS Gen2. You will guide architecture, optimize batch and streaming pipelines, and ensure governance and security across data platforms.

You will mentor engineers, collaborate with product and analytics teams, and define reusable workflows for efficient data delivery. Strong Azure expertise and leadership are essential.