Lead Data Engineer: Data Visualization, ETL & Data Warehousing

Job Summary:

Lead Data Engineer

Key Responsibilities:

• Design and implement enterprise dashboards and visualizations using

  ThoughtSpot

  (preferred),

  Tableau

  , and

  Power BI

  .
• Build and optimize data architectures on

  Snowflake

  ,

  Databricks

  , and other cloud platforms.

• Lead the end-to-end development

  of scalable ETL pipelines and data solutions to support enterprise analytics and reporting.
• Serve as a technical expert and mentor to junior engineers and analysts on data modeling, ETL design, and best practices.
• Collaborate with cross-functional teams including data science, product, and business stakeholders to understand data needs and deliver solutions.
• Establish and enforce data engineering standards, code reviews, and performance optimization practices.
• Own data quality, integrity, and reliability across the full data pipeline.
• Drive the adoption of best practices in ETL orchestration, monitoring, and documentation.
• Evaluate new technologies and tools to continuously improve the data ecosystem.

Required Qualifications:

• 810 years of progressive experience in

  data engineering

  ,

  ETL development

  , and

  business intelligence

  .
• Proven leadership in designing and deploying large-scale

  data pipelines

  and

  data architecture

  .
• Expertise in

  SQL

  and experience optimizing complex queries across large datasets.
• Strong experience in

  ETL tools

  and frameworks (e.g., dbt, Airflow, Informatica, Talend, custom scripting).
• Hands-on experience with cloud-based data platforms:

• Snowflake

• Databricks

• Proficiency in data visualization using:

• ThoughtSpot

  (preferred)

• Tableau

• Power BI

• In-depth understanding of

  data warehousing

  ,

  dimensional modeling

  , and

  data governance

  .
• Excellent communication skills with the ability to lead technical discussions and influence stakeholders.

Preferred Qualifications:

• Experience integrating ThoughtSpot with cloud data platforms.
• Proficiency in scripting languages such as

  Python

  .
• Familiarity with

  CI/CD pipelines

  ,

  Git

  , and Agile methodologies.

AWS

Why Join Us?

• Lead data engineering initiatives that directly impact strategic decision-making.
• Work with a modern, cloud-native data stack and enterprise-grade tools.
• Collaborate with a high-performing team in a fast-paced, data-driven environment.
• Competitive compensation, leadership opportunities, and flexible work options.