Senior Data Engineer

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

Job summary

Evnek in Bengaluru seeks a Senior Data Engineer to lead enterprise-scale data initiatives, shaping cloud-native platforms and modern data ecosystems. The role demands architectural vision, hands-on delivery, and leadership across multiple teams to drive data modernization.

You will architect Lakehouse solutions, govern data quality, and collaborate with stakeholders to translate requirements into scalable technical designs ensuring reliability and performance.

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.

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.

Skills

Python

Scala

Leadership

Data modeling

Cloud architecture

Stakeholder management

Communication

Problem solving

Education

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

Tools

Databricks

Apache Spark

Snowflake

Kafka

Azure

Terraform

Azure Data Factory

Azure Synapse

Data Lake Storage

Lakehouse

Job description

Job Title: Senior Data Engineer Experience: 6–12 Years Location: Bengaluru Notice Period: Immediate or 15days

Job Summary

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