Data Engineer Lead

TechDigital Group; Fremont (CA); On-site; USD 90,000 - 120,000; Full time

Job summary

A leading technology solutions provider in California seeks a talented data engineer to design enterprise-grade data solutions using Azure and Microsoft Fabric. The role includes mentoring team members and ensuring best practices in data governance and compliance. Ideal candidates should have strong experience with data Lakehouse solutions and collaboration with cross-functional teams.

Qualifications

• Experience designing enterprise-grade data solutions using Azure.
• Knowledge of data governance, security, and compliance.
• Ability to mentor and guide data engineers.

Responsibilities

• Design and implement data Lakehouse Solutions leveraging OneLake.
• Collaborate with cross-functional teams to translate business needs.
• Drive best practices in data engineering including CI/CD.

Skills

Microsoft Fabric

Microsoft Azure

Data streaming

infrastructure-as-code

SQL

Python

Spark

Job description

Top must have skills

• Microsoft Fabric.
• Microsoft Azure: Azure Data Factory, Azure Synapse, Azure Databricks, Azure SQL, Event Hub
• Data streaming (e.g., Azure Event Hubs, Kafka)
• infrastructure-as-code (e.g., Terraform, ARM templates)
• SQL, Python, and Spark.

Job Description

• Design and implementation of enterprise-grade data solutions using Azure and Microsoft Fabric.
• Design and implement data Lakehouse Solutions leveraging OneLake, Delta Lake, and Direct Lake mode in Power BI.
• Define and enforce data engineering best practices, including CI/CD, versioning, testing, and monitoring.
• Collaborate with cross-functional teams including data scientists, analysts, and business stakeholders to translate business needs into technical solutions.
• Drive data governance, security, and compliance across all data assets.
• Mentor and guide data engineers, fostering a culture of innovation and excellence.
• Evaluate and integrate new tools and technologies to enhance data capabilities.
• Own the data lifecycle, from ingestion and transformation to consumption and visualization