Senior Lead -Business Intelligence

About us

Launched in 2017, WeWork India is one of India’s leading premium flexible workspace operators - GPTW certified (Nov 2024 – Nov 2025, Dec 2025 – Dec 2026). WeWork India has been the largest operator by total revenue for the past three fiscal years*. Since its inception, WeWork India has expanded across 8 cities in Chennai, New Delhi, Gurugram, Noida, Mumbai, Bengaluru, Pune, and Hyderabad, with 73 operational centres spanning 8.2 million square feet (as of December 2025). WeWork India has played a significant role in the growth of the flexible workspace sector and contributed to the evolution of its products and services, providing customized and curated solutions for various office space needs*.

For more information, please visit our website

About the role

As an Analytics Engineer, the candidate will play a key role in bridging the gap between our data engineering and analytics teams. The candidate will own the transformation layer of our data stack, turning raw data into clean, reliable, and well-documented datasets that power decision-making across the company. The candidate will work closely with data engineers, analysts, and business stakeholders to build the semantic layer that makes data usable at scale.

To do well in this role, candidates need to have a very fine eye for detail, experience as a business data analyst, and deep understanding of the popular data analysis tools and databases, with the goal of providing the insights required to power our organization’s growth. The candidate will work closely with multidisciplinary teams and leadership to collect and analyze the data from various sources. Particularly important to the role is the ability to communicate effectively and to maintain open lines of communication with team members and stakeholders.

Roles and responsibilities

• Architect, construct, and oversee data models within our Snowflake warehouse utilizing dbt.
• Take ownership of the transformation layer, converting raw source data into sets ready for advanced analytics.
• Collaborate with analysts and business stakeholders to identify requirements and develop scalable data models.
• Execute data quality assessments, monitoring, and documentation to maintain a high level of trust in our data.
• Establish and manage essential business metrics within a unified semantic layer.
• Enhance query efficiency and manage warehouse expenditure through optimization.
• Define and promote best practices for version control, CI/CD, and peer reviews for all analytics code.
• Provide mentorship to analysts regarding SQL best practices and core dimensional modeling principles.
• Play a contributing role in the refinement of our overarching data strategy and architectural framework.

Experience and qualifications

• Over 7 to 10 years of professional experience in analytics engineering, data engineering, or a comparable technical role.
• Advanced proficiency in SQL, with expertise in intricate transformations, window functions, and performance tuning.
• Direct experience using dbt or similar tools, alongside orchestration frameworks like Airflow.
• Solid grasp of data modeling methodologies, particularly with Snowflake schemas.
• Familiarity with cloud-based data warehouses such as Snowflake, BigQuery, Redshift, or Databricks.
• Skilled in Git and modern engineering workflows, including version control, code review, and CI/CD.
• Working knowledge of Python for developing scripts and automating processes.
• Experience with BI platforms, where knowledge of Tableau is considered a distinct advantage.
• Previous exposure to product analytics platforms like Amplitude, Mixpanel, or Snowplow is preferred.
• Excellent communication skills with the ability to bridge the gap between business queries and data-driven solutions.