Senior Data Engineer

Velocitai Digital; Gurugram District; On-site; INR 1,800,000 - 3,000,000; Full time

Benefits offered by this job

Health insurance

Performance bonuses

Professional development

Job summary

Velocitai Digital is seeking a Data Engineer to design and implement scalable ETL pipelines for large, diverse datasets. You will build and optimize data lakes and data warehouses, support advanced analytics, and ensure governance and compliance across data workflows.

You will collaborate with data scientists, analysts, and software engineers to migrate sources into centralized repositories, improve data accessibility, and reduce processing costs while maintaining high data quality.

Qualifications

• Strong experience in designing and building scalable ETL pipelines.
• Proficiency in data lakes and data warehouses architectures.
• Hands-on with large-scale data processing systems in production.
• Experience aligning data models with regulatory requirements.

Responsibilities

• Design and build scalable ETL pipelines for large data sets.
• Develop and manage data lakes, warehouses, and processing systems.
• Optimize data retrieval, troubleshoot bottlenecks, and reduce costs.
• Collaborate with data scientists and engineers across time zones.
• Ensure data quality, governance, and compliance in data workflows.
• Deliver BI solutions and support reporting needs across teams.
• Monitor pipeline health and resolve incidents affecting downstream users.
• Document processes and data mappings for continuity.

Skills

ETL design

Data engineering

SQL

Python

Spark

Education

Bachelors in Statistics/CS/IT

Masters in CS/Data Engineering/IS

Tools

Azure

Databricks

Snowflake

Power BI

Job description

Role & responsibilities

• Design and build scalable Extract, Transform, Load (ETL) pipelines to process large-scale structured and unstructured data, ensuring alignment with enterprise data architecture standards and pharmaceutical distribution data models.
• Develop and manage data architectures, including data lakes, data warehouses, and large-scale processing systems that support advanced analytics capabilities across the organization.
• Optimize data retrieval processes, troubleshoot pipeline bottlenecks, and fine-tune database performance to maximize efficiency and reduce processing costs.
• Interpret data sets with particular attention to trends and patterns valuable for diagnostic and

predictive analytics efforts, creating visual representations of quantitative and qualitative data to support business decision-making.

• Implement data quality and governance processes, including validation checks, error handling, and quarantine procedures to ensure data accuracy, consistency, and compliance with applicable regulatory requirements.

• Support the delivery of Business Intelligence solutions to internal and external customers, utilizing business intelligence tools across departments and functional areas to provide detailed reporting and analysis.
• Assess analytics and reporting needs, provide recommendations for enhanced solutions and specifications for business intelligence tools, and prioritize reporting requirements across process areas to align with deployment strategies.
• Monitor pipeline health, system integrity, and automated alerts proactively, diagnosing and resolving incidents involving Extract, Transform, Load scripts, database connectivity, or infrastructure issues to minimize impact on downstream consumers.
• Collaborate with data scientists, analysts, software engineers, and operations teams on system upgrades, migrations, and integration projects, onboarding new data sources from various applications and interfaces into central repositories.
• Maintain data management standards and processes to effectively govern data through the reporting life cycle, proactively identifying opportunities for continuous improvement and operational excellence.
• Validate data for accuracy, process audit reports, propose solutions to remedy deficiencies, and confirm results in accordance with applicable data compliance requirements.
• Communicate data engineering requirements, architecture decisions, and technical findings to cross-functional partners across multiple time zones, providing expertise and guidance on data infrastructure and pipeline design.
• Document processes, standard operating procedures, source-to-target mappings, and knowledge artifacts to ensure operational continuity during transitions, enabling seamless integration of evolving team structures.

Qualifications

Education

• Bachelors degree in Statistics, Computer Science, Information Technology, or equivalent related experience (required).
• Masters degree in Computer Science, Data Engineering, Information Systems, or a related technical discipline (preferred).

Experience

• Minimum professional experience as per the Level in data engineering, with a focus on designing, building, and maintaining scalable data pipelines and data architectures in enterprise environments.
• Minimum of hands-on experience as per the Level developing and deploying Extract, Transform,

Load (ETL) pipelines, data lakes, data warehouses, and large-scale data processing systems in production environments.

Certifications (Required / Preferred)

• Microsoft Certified: Azure Data Engineer Associate (DP-203) Required.
• Databricks Certified Data Engineer Associate — Required.
• Microsoft Certified: Power BI Data Analyst Associate — Preferred.
• Snowflake SnowPro Core Certification — Preferred.