Senior Data & Analytics Engineer (5-10 yrs)

Sr. Data & Analytics Engineer

Location : India (Hybrid/Remote)

Experience : 5- 10 Years

Employment Type : Full-Time

About the Role :

We are seeking a highly analytical and technically strong Sr. Data & Analytics Engineer to bridge the gap between business insights and scalable data infrastructure. This role will be responsible for designing data pipelines, transforming raw data into actionable intelligence, enabling self-service analytics, and supporting advanced reporting and AI-driven initiatives.

The ideal candidate combines strong business acumen with hands-on expertise in data engineering, data modeling, cloud platforms, and analytics tools.

Key Responsibilities :

Data Engineering & Platform Development :

- Design, build, and maintain scalable ETL/ELT pipelines from multiple enterprise systems.

- Develop robust data integration frameworks to support reporting, analytics, and operational use cases.

- Implement data quality controls, validation mechanisms, and monitoring processes.

- Build and optimize data models, data marts, and enterprise datasets.

- Automate data ingestion, transformation, and orchestration workflows.

- Support migration and modernization of legacy data environments to cloud-based architectures.

Data Analytics & Business Intelligence :

- Translate business requirements into dashboards, reports, and analytical solutions.

- Develop KPIs, metrics, and executive reporting frameworks.

- Perform trend analysis, forecasting, and root-cause investigations.

- Create scalable semantic models to enable self-service reporting.

- Partner with business stakeholders to identify opportunities for data-driven decision making.

- Deliver actionable insights that improve operational efficiency and business performance.

Data Governance & Quality :

- Establish data governance standards, metadata management, and documentation practices.

- Define and maintain data lineage and business glossary artifacts.

- Ensure compliance with data security, privacy, and regulatory requirements.

- Collaborate with data owners and business teams to improve data accuracy and consistency.

Advanced Analytics & AI Enablement :

- Prepare curated datasets for predictive analytics and AI/ML initiatives.

- Support development of AI-powered reporting and analytics solutions.

- Work closely with data scientists and AI teams to operationalize analytical models.

- Evaluate emerging technologies in data engineering, analytics, and AI ecosystems.

Required Qualifications :

- Bachelor's or Master's degree in Computer Science, Information Systems, Data Science, Engineering, Mathematics, or related discipline.

- 5+ years of experience in Data Engineering, Data Analytics, or Business Intelligence roles.

- Strong expertise in SQL and data modeling techniques.

- Hands-on experience with Python for data processing and automation.

- Experience building ETL/ELT pipelines using modern data integration tools.

- Strong understanding of data warehousing concepts and dimensional modeling.

Experience with cloud data platforms such as :

- AWS

- Azure

- Google Cloud Platform (GCP)

Experience with BI and visualization tools :

- Power BI

- Tableau

- Looker

- Qlik

Preferred Qualifications :

Experience with modern data platforms such as :

- Databricks

- Snowflake

- BigQuery

- Redshift

- Synapse Analytics

- Knowledge of Apache Spark and distributed data processing.

- Experience with workflow orchestration tools such as Airflow.

- Exposure to DataOps, DevOps, and CI/CD practices.

- Familiarity with AI, Machine Learning, and Generative AI use cases.

- Experience working in enterprise environments supporting Finance, Sales, Operations, or Customer Analytics.

Technical Skills :

Data Engineering :

- SQL

- Python

- Spark

- ETL/ELT Development

- Data Warehousing

- Data Lakes

- API Integration

Analytics & Reporting :

- Power BI

- Tableau

- Looker

- KPI Design

- Statistical Analysis

- Forecasting

Cloud & Platforms :

- AWS

- Azure

- GCP

- Snowflake

- Databricks

- BigQuery

Governance :

- Data Quality

- Data Cataloging

- Metadata Management

- Data Lineage

- Data Security

Success Metrics :

- Improved data availability and reliability across business functions.

- Reduced manual reporting effort through automation.

- Increased adoption of self-service analytics.

- Enhanced data quality and governance compliance.

- Faster delivery of business insights and analytical solutions.

- Successful enablement of AI and advanced analytics initiatives.

What Makes This Role Unique :

This is not a traditional reporting-focused Data Analyst position nor a pure Data Engineering role. The successful candidate will own the full data lifecyclefrom ingestion and transformation to business insights and AI readinessserving as a strategic partner in the organization's data-driven transformation journey.