Senior Data Engineer

Space Inventive; Hyderabad; Hybrid; INR 1,500,000 - 2,100,000; Full time

Job summary

Space Inventive is seeking an experienced Senior Data Engineer in Hyderabad to lead end-to-end data engineering initiatives. The role requires deep expertise in SQL, ETL development, Databricks, and Pharma Market Access data to design, develop, and deploy scalable data solutions.

You will own the lifecycle from requirements gathering to production deployment, collaborate with stakeholders, and ensure robust data models and pipelines across cloud platforms.

Qualifications

• 7+ years of experience in Data Engineering, Data Warehousing, and ETL development.
• Advanced SQL, including query optimization, performance tuning, stored procedures, and complex data transformations.
• Proven expertise in Snowflake, PySpark for large-scale data processing.
• Experience building and maintaining end-to-end ETL/ELT pipelines in cloud-based environments.
• Strong experience in the Pharmaceutical/Life Sciences domain, with a focus on Market Access data.
• Strong understanding of data modeling, data warehousing concepts, and data architecture best practices.
• Demonstrated ability to independently manage and deliver end-to-end projects, from requirement gathering through deployment and production support.

Responsibilities

• Own and manage the end-to-end delivery of data engineering projects.
• Design, develop, optimize, and maintain complex data pipelines using modern ETL frameworks.
• Build scalable and high-performance data solutions leveraging cloud-based data platforms.
• Develop advanced SQL queries, stored procedures, and data transformation logic for large-scale datasets.
• Work closely with business stakeholders to translate requirements into technical solutions.
• Collaborate with cross-functional teams to ensure data integration from multiple sources.
• Perform root cause analysis and provide production support for data-related issues.
• Drive best practices in data engineering, code quality, documentation, and performance optimization.

Skills

Advanced SQL

ETL development

Snowflake

PySpark

Data warehousing

Pharma Market Access domain

Tools

Databricks

Snowflake

Job description

Job Summary

We are seeking an experienced Senior Data Engineer with strong expertise in SQL, ETL development, Databricks, and Pharma Market Access data to support and lead end-to-end data engineering initiatives. The ideal candidate will be responsible for designing, developing, and maintaining scalable data solutions while owning the complete project lifecycle from requirements gathering through production deployment and support.

Key Responsibilities

• Own and manage the end-to-end delivery of data engineering projects.


• Design, develop, optimize, and maintain complex data pipelines using modern ETL frameworks.


• Build scalable and high-performance data solutions leveraging cloud-based data platforms.


• Develop advanced SQL queries, stored procedures, and data transformation logic for large-scale datasets.


• Work closely with business stakeholders, data analysts, and product teams to understand requirements and translate them into technical solutions.


• Collaborate with cross-functional teams to ensure seamless integration of data from multiple sources.


• Perform root cause analysis and provide production support for data-related issues.


• Drive best practices in data engineering, code quality, documentation, and performance optimization.

Qualifications:

• 7+ years of experience in Data Engineering, Data Warehousing, and ETL development.


• Strong hands-on experience with Advanced SQL, including query optimization, performance tuning, stored procedures, and complex data transformations.


• Proven expertise in Snowflake, PySpark for large-scale data processing.


• Experience building and maintaining end-to-end ETL/ELT pipelines in cloud-based environments.


• Strong experience in the Pharmaceutical/Life Sciences domain, with a focus on Market Access data.


• Strong understanding of data modeling, data warehousing concepts, and data architecture best practices.


• Demonstrated ability to independently manage and deliver end-to-end projects, from requirement gathering through deployment and production support.