Data Engineers

Team: IT

Location: India

Commitment: Full-time

Workplace Type: remote

Accountabilities

• Design, build, and maintain BigQuery datamarts and analytical tables for BI reporting and analytics.
• Develop scalable data models using star schema, snowflake, dimensional, and denormalized approaches.
• Optimize query performance, storage efficiency, and data warehouse workloads.
• Build and maintain data pipelines for ingestion, transformation, and loading into analytics environments.
• Develop transformation workflows using SQL, dbt, or similar data transformation frameworks.
• Implement data validation and quality controls to maintain accuracy and consistency across datasets.
• Establish and maintain data standards, naming conventions, schema management, documentation, and version control.
• Monitor data pipelines, troubleshoot failures, and resolve data inconsistencies.
• Collaborate with BI teams to ensure datasets meet semantic-layer and dashboard requirements.
• Deliver optimized, analytics-ready datasets that minimize complex transformations within BI tools.
• Contribute to continuous improvements in data architecture, engineering processes, and analytics workflows.

Requirements:

• 3+ years of experience in Data Engineering, Analytics Engineering, or a closely related field.
• Strong SQL expertise, particularly for analytical workloads and complex data transformations.
• Hands-on experience with cloud data warehouses such as BigQuery, Amazon Redshift, Snowflake, or similar platforms.
• Proven experience designing dimensional, star-schema, or other scalable data models.
• Experience building and maintaining analytics-ready datamarts.
• Strong understanding of data warehousing, data pipelines, data modeling, and BI/analytics requirements.
• Experience with dbt or similar data-transformation frameworks is preferred.
• Familiarity with Git-based development workflows and CI/CD for data pipelines is an advantage.
• Experience working with BI platforms such as Looker, Tableau, or Power BI is a plus.
• Familiarity with retail or multi-location data environments is beneficial.
• Strong analytical, problem-solving, documentation, and collaboration skills.
• Knowledge of prompt engineering and AI-assisted workflows is an advantage.

Benefits:

• Fully remote work environment.
• Full-time position.
• Compensation of up to $17 per hour.
• Opportunity to work with modern cloud data warehousing and analytics technologies.
• Hands-on experience with BigQuery, data modeling, datamarts, and scalable data pipelines.
• Collaboration with BI and analytics teams on business-critical datasets.
• Exposure to modern data engineering practices, including dbt, Git, CI/CD, and AI-assisted workflows.