D 365- Data Engineer

We are seeking a highly skilled Senior Data Engineer with 8–12 years of experience in designing, developing, and managing scalable data platforms and enterprise data solutions. The ideal candidate will have strong expertise in data engineering, cloud technologies, ETL/ELT development, data warehousing, and big data ecosystems.
The candidate will play a key role in building modern data platforms, enabling advanced analytics, business intelligence, AI/ML initiatives, and data-driven decision-making across the organization.
Qualification:
Required Technical Skills
Data Engineering
Data Modeling (Dimensional & Relational)
ETL/ELT Development
Data Warehousing Concepts
Data Lake & Lakehouse Architecture
Data Migration & Data Integration
Real-Time Data Processing
Cloud Platforms (Any One or More)
Microsoft Azure
Azure Data Factory (ADF)
Azure Synapse Analytics
Azure Data Lake Storage (ADLS)
Azure Databricks
Microsoft Fabric
AWS
Glue
Redshift
EMR
S3
Google Cloud Platform (GCP)
BigQuery
Dataflow
Cloud Storage
Big Data Technologies
Apache Spark
Databricks
Hadoop Ecosystem
Kafka
Delta Lake
Databases
SQL Server
Oracle
PostgreSQL
MySQL
Snowflake
Azure SQL Database
Programming Skills
Python
SQL
PySpark
Scala (Preferred)
Shell Scripting
DevOps & Version Control
Azure DevOps
Git
CI/CD Pipelines
Jenkins
Required Experience
8–12 years of overall IT experience.
Minimum 5+ years of experience in Data Engineering.
Strong hands-on expertise in SQL and Python.
Experience with cloud-based data platforms (Azure preferred).
Expertise in building data pipelines, ETL/ELT frameworks, and data warehouses.
Experience working with large-scale structured and unstructured datasets.
Knowledge of data governance, security, and compliance frameworks.
Experience in Agile/Scrum delivery models.
Preferred Qualifications
Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or related field.
Microsoft Certified: Azure Data Engineer Associate (DP-203).
Microsoft Fabric Certification.
Databricks Certified Data Engineer.
AWS or GCP Data Engineering Certifications.
Key Responsibilities:
Design, develop, and maintain scalable data pipelines and data integration frameworks.
Build and optimize ETL/ELT processes for structured and unstructured data sources.
Develop and manage enterprise data warehouses, data lakes, and lakehouse architectures.
Implement data ingestion, transformation, and orchestration solutions using cloud-native services.
Collaborate with business analysts, data scientists, architects, and stakeholders to understand data requirements.
Ensure data quality, governance, security, and compliance standards are met.
Optimize database and query performance for large-scale datasets.
Design and implement real-time and batch data processing solutions.
Support reporting, analytics, AI/ML, and advanced data engineering initiatives.
Participate in architecture reviews and provide technical leadership to the data engineering team.
Develop CI/CD pipelines and automate deployment processes for data platforms.
Mentor junior engineers and establish engineering best practices.