Data Engineer - Assistant Manager

Kavi Software Technologies; Chennai District; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

Kavi Software Technologies in Chennai is seeking an experienced Assistant Manager Data Engineering to lead the design, development and optimization of enterprise-scale data platforms. You will drive scalable data pipelines and data architectures, while mentoring engineers and collaborating with business stakeholders.

Ideal candidates will have strong cloud experience (Azure, AWS, GCP), hands-on ETL/ELT delivery, and a passion for governance, security, and high availability.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field.
• 812 years of experience in Data Engineering, Data Warehousing, or Big Data technologies.
• Strong expertise in SQL and programming languages such as Python, Java, or Scala.
• Hands-on experience building large-scale ETL/ELT pipelines using Apache Airflow, DBT, or similar orchestration tools.
• Strong experience with cloud platforms such as Azure, AWS, or Google Cloud Platform (GCP).
• Experience with enterprise data warehouse technologies such as Snowflake, Redshift, BigQuery, Azure Synapse, or Databricks.
• Strong knowledge of Spark, Kafka, Hadoop, and distributed data processing frameworks.
• Solid understanding of data modelling, dimensional modelling, schema design, and data governance principles.
• Experience implementing CI/CD, Infrastructure as Code, and DevOps practices for data platforms.
• Strong analytical, troubleshooting, and problem-solving skills.
• Excellent communication and stakeholder management skills.
• Experience mentoring technical teams and driving engineering best practices.

Responsibilities

• Lead the design, development, and maintenance of scalable data pipelines, ETL/ELT processes, and data integration solutions.
• Design and implement robust, high-performance data architectures that support analytics, reporting, and business intelligence.
• Drive data quality, governance, security, and compliance initiatives across the data platform.
• Collaborate with business stakeholders, product owners, data scientists, and engineering teams to gather requirements and deliver data solutions.
• Provide technical leadership, mentor junior and senior data engineers, and establish engineering best practices.
• Optimize data processing workflows for performance, scalability, and cost efficiency.
• Implement and maintain CI/CD pipelines, automation, and monitoring for data engineering workloads.
• Review solution designs, perform code reviews, and ensure adherence to coding standards and architectural best practices.
• Troubleshoot complex production issues and ensure high availability and reliability of data platforms.
• Stay current with emerging technologies and recommend improvements to the organization's data engineering capabilities.

Skills

SQL

Python

Java

Scala

Airflow

DBT

Azure

AWS

GCP

Snowflake

Redshift

BigQuery

Azure Synapse

Databricks

Spark

Kafka

Hadoop

Data Modeling

CI/CD

DevOps

ETL/ELT

Data Governance

Leadership

Mentoring

Communication

Education

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

Tools

Apache Airflow

DBT

Snowflake

Redshift

BigQuery

Databricks

Azure Synapse

Job description

We are looking for an experienced Assistant Manager Data Engineering to lead the design, development, and optimization of enterprise-scale data platforms. The ideal candidate will have strong expertise in modern data engineering technologies, cloud platforms, and data architecture, while also providing technical leadership, mentoring engineers, and collaborating with business stakeholders to deliver scalable, high-quality data solutions.

Key Responsibilities

• Lead the design, development, and maintenance of scalable data pipelines, ETL/ELT processes, and data integration solutions.
• Design and implement robust, high-performance data architectures that support analytics, reporting, and business intelligence.
• Drive data quality, governance, security, and compliance initiatives across the data platform.
• Collaborate with business stakeholders, product owners, data scientists, and engineering teams to gather requirements and deliver data solutions.
• Provide technical leadership, mentor junior and senior data engineers, and establish engineering best practices.
• Optimize data processing workflows for performance, scalability, and cost efficiency.
• Implement and maintain CI/CD pipelines, automation, and monitoring for data engineering workloads.
• Review solution designs, perform code reviews, and ensure adherence to coding standards and architectural best practices.
• Troubleshoot complex production issues and ensure high availability and reliability of data platforms.
• Stay current with emerging technologies and recommend improvements to the organization's data engineering capabilities.

Required Qualifications & Skills

• Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field.
• 812 years of experience in Data Engineering, Data Warehousing, or Big Data technologies.
• Strong expertise in SQL and programming languages such as Python, Java, or Scala.
• Hands-on experience building large-scale ETL/ELT pipelines using Apache Airflow, DBT, or similar orchestration tools.
• Strong experience with cloud platforms such as Azure, AWS, or Google Cloud Platform (GCP).
• Experience with enterprise data warehouse technologies such as Snowflake, Redshift, BigQuery, Azure Synapse, or Databricks.
• Strong knowledge of Spark, Kafka, Hadoop, and distributed data processing frameworks.
• Solid understanding of data modelling, dimensional modelling, schema design, and data governance principles.
• Experience implementing CI/CD, Infrastructure as Code, and DevOps practices for data platforms.
• Strong analytical, troubleshooting, and problem-solving skills.
• Excellent communication and stakeholder management skills.
• Experience mentoring technical teams and driving engineering best practices.

Preferred Qualifications

• Experience with real-time data streaming and event-driven architectures.
• Exposure to Machine Learning pipelines and MLOps.
• Experience leading data engineering projects or managing small technical teams.
• Relevant cloud certifications (Azure, AWS, or GCP) are a plus.