Data Engineer – Migration,Pipeline and Visualization

Position Title: Data Engineer – Migration,Pipeline and Visualization

Institute: Navodaya Education Trust

Location: Raichur Karnataka

About the Role

This is the most critical role in the early phase of our transformation. You will lead the data migration from manual records (Excel, paper registers, legacy systems) into our AWS cloud and design the continuous pipeline that keeps our on-premise data center synchronized. Your work will ensure that Navodaya has clean, reliable, and sovereign data – the foundation of everything we build.

Key Responsibilities

Data Migration

Inventory Data Sources: Identify all manual data sources across 8

institutions

Data Profiling: Analyze data quality, completeness, consistency, duplicates

Define Data Mapping: Create mapping rules from source fields to target

schema

Build ETL Pipelines: Use AWS Glue / Python to extract, cleanse, transform,

and load data

Validate Data: Run data reconciliation (row counts, key fields, sample

validation)

Document Lineage: Maintain data lineage documentation for DPDPA

compliance

Design Pipeline Architecture: Data flow from AWS staging → On-Prem

SOR

Implement Sync Jobs: Build scheduled sync jobs (EventBridge + Glue +

Python)

Set up Reconciliation: Automated data reconciliation between AWS and On-

Prem

Monitoring & Alerting: Set up CloudWatch alarms for pipeline failures

Phase 3: Data Quality & KPIs

Define Data Quality Metrics: Completeness, accuracy, timeliness,

consistency, uniqueness

Build Dashboards: For leadership to monitor pipeline health and data quality

Implement Validation Rules: Automated checks before data enters On-Prem

Data Governance: Work with CTO to define retention, archiving, and deletion

policies

Required Skills & Experience

Category - Requirement

Experience - 5-10 years in data engineering, including data migration projects

SQL - Advanced (PostgreSQL, Oracle, or SQL Server)

ETL - AWS Glue (or similar: Apache Airflow, Talend, Informatica)

Python Advanced (Pandas, PySpark, boto3)

Data Modeling - Star schema, 3NF, data vault (intermediate)

Data Profiling - Experience with data quality tools (Great Expectations, Deequ)

Data Visualization - Tableau, PowerBI

Cloud - AWS (S3, RDS, Glue, Lambda) – intermediate

Version Control - Git (basic)

Good-to-Have

Experience with healthcare or education data (sensitive data handling)

Knowledge of DPDPA (India's Data Protection Act) compliance

Experience with data cataloging tools (AWS Glue Data Catalog, Amundsen)

Experience with data visualization (PowerBI, Tableau, Metabase)

Experience working with legacy systems (Excel, paper records)