Lead Data Engineer

What You Will Do:

Following are high level responsibilities that you will play but not limited to:

• Lead the design, development, and implementation of modern data pipelines, data models, and ETL/ELT processes.
• Architect and optimize data lake and warehouse solutions using Microsoft Fabric, Databricks, or Snowflake.
• Enable business analytics and self-service reporting through Power BI and other visualization tools.
• Collaborate with data scientists, analysts, and business users to deliver reliable and high-performance data solutions.
• Implement and enforce best practices for data governance, data quality, and security.
• Mentor and guide junior data engineers; establish coding and design standards.
• Evaluate emerging technologies and tools to continuously improve the data ecosystem.

Required Qualifications:

• Bachelor's degree in computer science, Information Technology, Engineering, or a related field.
• Bachelors/Masters degree in Computer Science, Information Technology, Engineering, or related field.
• 8+ years of experience in data engineering or data platform development, with at least 23 years in a lead or architect role.
• Strong hands-on experience in one or more of the following:
• Microsoft Fabric (Data Factory, Lakehouse, Data Warehouse)
• Databricks (Spark, Delta Lake, PySpark, MLflow)
• Snowflake (Data Warehousing, Snowpipe, Performance Optimization)
• Power BI (Data Modeling, DAX, Report Development)
• Proficiency in SQL and programming languages like Python or Scala.
• Experience with Azure, AWS, or GCP cloud data services.
• Solid understanding of data modeling, data governance, security, and CI/CD practices.

Preferred Qualifications:

• Familiarity with data modeling techniques and practices for Power BI.
• Knowledge of Azure Databricks or other data processing frameworks.
• Knowledge of Microsoft Fabric or other Cloud Platforms.