ModMed - Data Engineer II

Description :

Key Responsibilities :

- Design, build, and maintain scalable data models and transformations using Databricks (Spark SQL, Delta Lake) and dbt

- Support and execute BI platform migrations (e.g., Qlik to ThoughtSpot, Tableau, or Power BI)

- Develop analytics-ready datasets and semantic layers to support business intelligence and self-service analytics

- Translate legacy QlikView/Qlik Sense logic (QVDs, scripting, set analysis) into modern data models

- Build and optimize complex analytics models and visualizations in ThoughtSpot or similar BI tools

- Ensure data quality, reliability, and performance through testing, monitoring, and optimization

- Write and optimize advanced SQL queries for complex transformations and reporting use cases

- Collaborate with stakeholders to understand analytical requirements and deliver scalable solutions

- Implement and support embedded analytics using ThoughtSpot Everywhere

- Manage and optimize Databricks SQL Warehouses, including Serverless configurations

- Apply best practices for data governance, security, and access control

Required Skills & Qualifications :

- 3+ years of hands-on experience as a Data Engineer, BI Developer, or Analytics Engineer

- Expert proficiency with Databricks (Spark SQL, Delta Lake) and dbt

- Strong experience in at least one BI platform migration project

- Deep working knowledge of QlikView or Qlik Sense, including QVDs, scripting, and set analysis

- Proven experience building analytics models and search-driven visualizations in ThoughtSpot or similar BI tools

- Advanced SQL skills with experience in query optimization and performance tuning

- Strong understanding of data warehousing concepts, including star and snowflake schemas

- Proficiency in Python for data processing, orchestration, or Databricks jobs

Nice-to-Have Skills :

- Experience with ThoughtSpot Everywhere for embedded analytics

- Hands-on experience administering or optimizing Databricks SQL Warehouses (Serverless)

- Familiarity with modern data governance tools and best practices