Senior Data Engineer

Evnek Technologies Pvt Ltd; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Evnek Technologies Pvt Ltd. seeks an experienced Lead Data Engineer to guide enterprise-scale data initiatives and modern cloud-native platforms. You will shape data architecture, lead top-performing teams, and deliver scalable data solutions for business stakeholders.

The role requires strong technical leadership, expertise in Lakehouse architectures, and hands-on collaboration across data, product, and operations teams. Excellent mentorship and governance focus are essential.

Qualifications

• 6–12 years of experience in Data Engineering, Data Platform Development, or Cloud Data Architecture.
• Proven experience leading enterprise-scale data engineering programs and cloud migration initiatives.
• Strong expertise in designing scalable, secure, and high-performance data platforms.
• Demonstrated experience leading and mentoring technical teams.
• Strong understanding of data modeling, data warehousing, Lakehouse architecture, and distributed data processing.
• Excellent analytical, problem-solving, and decision-making skills.
• Outstanding communication, stakeholder management, and client-facing skills.

Responsibilities

• Define and implement enterprise data architecture aligned with business and technology strategies.
• Lead multiple data engineering teams across complex enterprise projects and cloud transformations.
• Design, build, and optimize scalable cloud-native data platforms and modern data ecosystems.
• Architect and implement Lakehouse solutions using industry best practices.
• Drive enterprise-wide data governance, data quality, metadata management, and security initiatives.
• Review solution architecture, technical designs, and code to ensure adherence to standards.
• Collaborate with architects, product owners, business analysts, and stakeholders to translate requirements into scalable solutions.
• Ensure platform reliability, scalability, performance, and operational excellence.
• Champion automation, CI/CD, IaC, and DataOps best practices.
• Mentor and coach data engineers, fostering technical excellence and continuous learning.
• Identify opportunities for process improvements and technology modernization.
• Provide technical leadership from design through deployment and support.

Skills

Data architecture

Data engineering

Team leadership

Stakeholder management

Communication

Problem solving

CI/CD

DataOps

Cloud platforms

Mentoring

Education

Bachelor's or Master's in CS/IT/Engineering

Tools

Databricks

Snowflake

Apache Kafka

Azure

Terraform

Azure Data Factory

Azure Synapse

Azure Data Lake Storage

Job description

We are seeking an experienced and visionary Lead Data Engineer to lead enterprise-scale data engineering initiatives and drive the design, implementation, and modernization of cloud-native data platforms. The ideal candidate will have extensive experience in defining enterprise data architecture, leading high-performing engineering teams, and delivering scalable data solutions using modern cloud technologies. This role requires strong technical leadership, architectural expertise, and the ability to collaborate with cross-functional teams and business stakeholders.

Key Responsibilities

• Define and implement enterprise data architecture aligned with business and technology strategies.
  
• Lead multiple data engineering teams across complex enterprise projects and cloud transformation initiatives.
  
• Design, build, and optimize scalable cloud-native data platforms and modern data ecosystems.
  
• Architect and implement Lakehouse solutions using industry best practices.
  
• Drive enterprise-wide data governance, data quality, metadata management, and security initiatives.
  
• Review solution architecture, technical designs, and code to ensure adherence to engineering standards and best practices.
  
• Collaborate with Solution Architects, Product Owners, Business Analysts, and stakeholders to translate business requirements into scalable technical solutions.
  
• Ensure platform reliability, scalability, performance, and operational excellence.
  
• Champion automation, CI/CD, Infrastructure as Code (IaC), and DataOps best practices.
  
• Mentor and coach data engineers, fostering technical excellence and continuous learning.
  
• Identify opportunities for process improvements and technology modernization.
  
• Provide technical leadership throughout the software development lifecycle, from design through deployment and support.
  

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related discipline.
  
• 6–12 years of experience in Data Engineering, Data Platform Development, or Cloud Data Architecture.
  
• Proven experience leading enterprise-scale data engineering programs and cloud migration initiatives.
  
• Strong expertise in designing scalable, secure, and high-performance data platforms.
  
• Demonstrated experience leading and mentoring technical teams.
  
• Strong understanding of data modeling, data warehousing, Lakehouse architecture, and distributed data processing.
  
• Excellent analytical, problem-solving, and decision-making skills.
  
• Outstanding communication, stakeholder management, and client-facing skills.
  

Preferred Qualifications

• Experience with enterprise data governance frameworks and metadata management solutions.
  
• Knowledge of real-time streaming and event-driven architectures.
  
• Experience with Infrastructure as Code (Terraform), containerization, and orchestration technologies.
  
• Azure certifications or cloud architecture certifications are highly desirable.
  
• Familiarity with Agile, Scrum, and modern software engineering practices.
  

Requirements

Required Technical Skills

• Strong programming expertise in Python and Scala
  
• Extensive experience with Apache Spark
  
• Hands-on experience with Databricks
  
• Strong knowledge of Snowflake
  
• Experience with Apache Kafka and event-driven data architectures
  
• Deep expertise in Microsoft Azure cloud services
  
• Hands-on experience with:
  Azure Data Factory (ADF)
  Azure Synapse Analytics
  Azure Data Lake Storage
  
• Strong understanding of CI/CD pipelines and DevOps practices
  
• Experience implementing DataOps methodologies
  
• Knowledge of Terraform or other Infrastructure as Code (IaC) tools is highly preferred