Role & responsibilities

Key Responsibilities

- Design, develop, and maintain scalable data pipelines, ETL/ELT workflows, and data integration solutions.

- Develop and optimize complex SQL queries, views, stored procedures, and data models for analytics and operational reporting.

- Integrate data from REST APIs, Graph APIs, enterprise applications, databases, and cloud platforms.

- Process, transform, and manage structured, semi-structured, and unstructured data, including JSON.

- Design, implement, and support cloud-based data solutions on Azure or AWS.

- Troubleshoot and resolve data quality, synchronization, transformation, and integration issues.

- Collaborate with business and technical stakeholders to gather data requirements and deliver scalable integration solutions.

- Maintain technical documentation, data mappings, and integration workflows while adhering to data governance best practices.

Required Qualifications

- Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or a related field.

- 7+ years of experience in Data Engineering, Data Integration, or ETL development.

- Robust expertise in SQL, including joins, views, stored procedures, query optimization,



and performance tuning.

- Hands-on experience with REST APIs, Microsoft Graph APIs, and enterprise application integrations.

- Experience working with JSON, XML, and data transformation techniques.

- Strong understanding of data modeling, normalization, and relational database concepts.

- Experience with Azure services (Storage, Azure SQL, Logic Apps) or AWS services (Redshift, S3, Lambda, Glue).

- Experience with Microsoft Power Automate or Azure Logic Apps for workflow automation.

- Proficiency with Git, Visual Studio Code, and version control best practices.

- Strong analytical, troubleshooting, and problem-solving skills.

Preferred Skills

- Experience integrating with enterprise platforms such as ServiceNow, Dynatrace, SolarWinds, and Nexthink.

- Programming experience using Python for data processing and automation.

- Knowledge of data architecture, metadata management, and data governance principles.

- Experience supporting AI, automation, and cloud-native data solutions.

- Familiarity with Agile/Scrum development methodologies and DevOps practices.

📌 Data Engineer (Data & Integration Engineer) (Bengaluru)
🏢 cirruslabs
📍 Bengaluru