Lead Azure Data Engineer

Methodhub; Fremont (CA); Hybrid; USD 140,000 - 210,000; Full time

Job summary

Methodhub in Fremont, CA is seeking a Senior Data Engineering Lead with 8+ years of experience to design and lead data engineering, warehousing, and lake solutions on Azure. This role blends hands-on coding with strategic leadership and stakeholder management.

You will drive data warehouse architectures (Azure Synapse, Azure SQL, Redshift, Snowflake, BigQuery), implement Medallion Architecture, and mentor delivery teams while ensuring timely, high-quality results in a hybrid 3-day-office model.

Qualifications

• 8+ years of experience in modern data engineering, data warehousing and data lake technologies on cloud platforms.
• Strong Python, PySpark, and SQL coding skills with leadership responsibilities.
• Experience with Azure data services (Synapse, SQL) and cloud data architectures.
• Proven ability to lead development teams and manage stakeholders.

Responsibilities

• Design and lead data engineering, warehousing, and data lake initiatives on Azure.
• Mentor and lead delivery teams, ensure timelines and quality.
• Implement Medallion Architecture for data management.

Skills

Python

PySpark

SQL

Leadership

Tools

Databricks

Azure Synapse

Azure SQL

Redshift

Snowflake

BigQuery

ADF

Informatica

Talend

Job description

Location: Fremont, CA (Hybrid - 3days work from office)

Employment Time: Full-Time

About the role

We are seeking a highly experienced Senior Data Engineering Lead with minimum 8+ years' experience in modern data engineering, data warehousing and data lake technologies on Azure cloud platform. The successful candidate will possess a strong technical background and proven leadership skills to manage stakeholders, design, and lead development efforts.

Your role:

• Data Warehousing: Expertise in data warehouse best practices, development standards and methodologies. Minimum of 8 years of experience in modern data engineering, data warehousing (Azure Synapse, Azure SQL, Amazon Redshift, Snowflake or Google Big Query), and data lake technologies on the Azure cloud.
• Big Data Tools: Strong experience with platforms (mandatory) such as Databricks (preferable). Experience with Databricks is highly desirable but not mandatory.
• Must be able to implement Medallion Architecture for data management.
• Lead development teams, drive project timelines, and ensure high-quality deliverables.

Skills & experience

• Programming Skills: Stellar hands-on expertise in Python, PySpark, and SQL.
• Data Warehousing: Expertise in data warehouse best practices, development standards and methodologies. Minimum of 8 years of experience in modern data engineering, data warehousing (Azure Synapse, Azure SQL, Amazon Redshift, Snowflake or Google Big Query), and data lake technologies on the Azure cloud.
• Data Modeling Expertise: Minimum of 12 years of proven experience with SQL, schema design, and dimensional data modeling.
• Big Data Tools: Strong experience with platforms (mandatory) such as Databricks (preferable). Experience with Databricks is highly desirable but not mandatory.
• Cloud Data Engineering concepts: Experience with common ETL/ELT tools (ADF, Informatica, Talend) and implementing Medallion Architecture for data management.
• Data Management and Storage: Proficiency with Azure SQL Database, Azure Data Lake Storage, Azure Cosmos DB, Azure Blob Storage, etc.
• Analytical Skills: Strong analytical and problem-solving skills.
• Leadership: Lead development teams, drive project timelines, and ensure high-quality deliverables.