Solutions Architect

Cyient; Hyderabad; On-site; INR 4,200,000 - 7,000,000; Full time

Job summary

Cyient is seeking a highly experienced Senior Data Engineer to design, build, and optimize enterprise-scale data platforms in Hyderabad. You will drive modernization initiatives, mentor engineers, and collaborate with stakeholders to deliver secure, scalable analytics solutions.

You will lead data integration, warehousing, and cloud migrations using AWS and GCP, orchestrate ETL/ELT pipelines, and establish standards for data governance, quality, and observability.

Qualifications

• 14+ years of experience in Data Engineering, Data Warehousing, and Big Data technologies.
• Strong experience with cloud-based data platforms and modern data architectures.
• Experience leading large-scale data transformation programs and teams.
• Excellent communication and stakeholder management skills.

Responsibilities

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

Skills

Python

SQL

Hadoop Ecosystem

Kafka

Airflow

Databricks

AWS

Glue

Redshift

EMR

S3

GCP

BigQuery

Dataflow

Composer

Education

Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or a related field

Tools

Git

Jenkins

Terraform

Docker

Job description

• Design, build, and optimize scalable data pipelines for batch and real-time data processing.
• 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 Skills

• Python
• SQL
• Hadoop Ecosystem
• Kafka
• Airflow
• Databricks
• AWS
• Glue
• Redshift
• EMR
• S3
• GCP (Good to have)
• BigQuery
• Dataflow
• Composer

Database & Data Warehousing

• SQL Server
• Oracle
• Snowflake
• Redshift

DevOps & Automation

• Git
• Jenkins
• Terraform
• Docker

Data Governance

• Data Quality Frameworks
• Metadata Management
• 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 modern data architecture.
• Experience handling large-scale enterprise data transformation programs.
• Excellent communication, leadership, and stakeholder management skills.

Preferred Certifications

• Azure Solutions Architect Expert
• AWS Certified Data Analytics – Specialty
• Snowflake SnowPro Certification

We are seeking a highly experienced Senior Data Engineer with 14+ years of expertise in designing, developing, and managing large-scale data platforms and enterprise data solutions. The ideal candidate should have strong experience in data architecture, cloud technologies, ETL/ELT frameworks, data warehousing, big data ecosystems, and modern data engineering practices. The candidate will play a key role in driving data modernization initiatives, mentoring engineering teams, and collaborating with business stakeholders to deliver scalable and secure data solutions.