Key Responsibilities

- Design, build, and optimize scalable data pipelines for batch and real-time data processing.
- Architect enterprise-grade data platforms using cloud-native technologies.
- Develop and maintain robust ETL/ELT frameworks for integrating data from multiple sources.
- Lead data migration and modernization initiatives from legacy systems to cloud platforms.
- Ensure data quality, governance, security, and compliance across enterprise data ecosystems.
- Implement data models, data marts, and data warehouse solutions to support analytics and reporting.
- Collaborate with Data Scientists, BI teams, Product Owners, and business stakeholders.
- Optimize data processing performance, scalability, and cost efficiency.
- Establish best practices for data engineering, CI/CD, automation, monitoring, and observability.
- Mentor junior and senior engineers while driving technical excellence within the team.

Required SkillsData Engineering &
- Big Data
- Python
- SQL
- Apache Spark
- Hadoop Ecosystem
- Kafka
- Airflow
- Databricks

Cloud Platforms
- Azure (Preferred)
- Azure Data Factory (ADF)
- Azure Synapse Analytics
- Azure Data Lake Storage (ADLS)
- Azure Event Hub

- AWS

- Glue
- Redshift
- EMR
- S3

- GCP (Good to have)

- BigQuery
- Dataflow
- Composer

Database &
- Data Warehousing

- SQL Server
- PostgreSQL
- Oracle
- Snowflake
- Azure Synapse
- Redshift





DevOps &
- Automation

- Git
- Azure DevOps
- Jenkins
- Terraform
- Docker
- Kubernetes

Data Governance
- Data Quality Frameworks
- Metadata Management
- Data Lineage
- Data Security &
- Compliance
- Master Data Management (MDM)

Leadership Responsibilities
- Lead and guide a team of Data Engineers.
- Participate in architecture review boards and technical governance discussions.
- Define enterprise data engineering standards and best practices.
- Drive stakeholder management and business engagement.
- Support project estimation, planning, and execution.

Qualifications
- Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or a related field.
- 14+ years of experience in Data Engineering, Data Warehousing, and Big Data technologies.
- Strong experience in cloud-based data platforms and up-to-date data architecture.
- Experience handling large-scale enterprise data transformation programs.
- Excellent communication, leadership, and stakeholder management skills.

Preferred Certifications
- Microsoft Certified: Azure Data Engineer Associate
- Azure Solutions Architect Expert
- AWS Certified Data Analytics –
- Specialty
- Databricks Certified Data Engineer Professional
- Snowflake SnowPro Certification

📌 Solution Architect (Hyderabad)
🏢 Cyient
📍 Hyderabad