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. Skills: snowflake , Power Bi, Sql, Databricks, Python Experience: 7.00-12.00 Years