Data Engineer (Analytics & Integrations)

Data Engineer Analytics & Reporting Pipelines

5-8 years

Manjeera Trinity, Hyderabad

5:30 PM 2:30 AM (US Shift Timings

Full-Time

About the Role

We are seeking a Data Engineer to design, build, and optimize data pipelines and reporting modules for a next-generation AI-driven enterprise platform. The ideal candidate will have hands-on experience in ETL development, analytics, and secure data integrations, with expertise in Power BI and exposure to no-code/low-code tools for building lightweight reporting interfaces.

Key Responsibilities

• Design, build, and maintain ETL pipelines for structured and unstructured data.
• Develop data models and semantic layers to support analytics and reporting needs.
• Integrate data securely across multiple systems (HR, payroll, finance, benefits, and external APIs).
• Build and optimize real-time and batch pipelines for analytics workloads.
• Collaborate with business stakeholders to design Power BI dashboards and ensure self-service reporting.
• Leverage no-code/low-code tools to create front-end reporting or workflow automation modules.
• Implement data quality, validation, and governance processes.
• Ensure compliance, security, and access control for sensitive enterprise data.
• Work closely with backend and AI teams to make data AI-ready for predictive insights.
  

Required Skills & Qualifications

• 5–8 years of experience in Data Engineering / ETL / Analytics.
• Strong expertise in ETL pipeline design & optimization (SQL, Python, or Spark).
• Experience with data integration tools (Informatica, Talend, Azure Data Factory, or similar).
• Hands-on experience in Power BI (reporting, DAX, Power Query, semantic modeling).
• Knowledge of databases (SQL, NoSQL, Graph – Neo4j a plus).
• Experience in building secure API-based integrations between enterprise systems.
• Exposure to event-driven data pipelines (Kafka preferred).
• Familiarity with cloud platforms (Azure preferred) and data storage services (Data Lake, Blob, Synapse).
• Strong skills in data governance, quality, and compliance.
• Good communication and stakeholder collaboration skills.

Nice to Have

• Exposure to low-code/no-code platforms (Power Apps, AppSheet, or Bubble).
• Knowledge of machine learning data pipelines.
• Experience with modern data orchestration tools (Temporal, Airflow, DBT).
• Familiarity with Agile/Scrum delivery models.

Education

Bachelor’s/Master’s in Computer Science, Information Systems, Data Engineering, or related field (or equivalent experience).