Senior Data Engineering Lead

Lonvec Technologies Private Limited; Hyderabad; On-site; INR 3,500,000 - 5,500,000; Full time

Job summary

Lonvec Technologies Private Limited is seeking a Senior Data Engineering Lead with 7–10 years of experience to design and deliver scalable data platforms and enterprise data solutions. You will work across engineering, analytics, and business teams to implement robust data pipelines and cloud data platforms.

The role emphasizes hands-on leadership as an individual contributor, with focus on ETL/ELT workflows, data modelling, data warehousing, and modern cloud-native architectures using Spark,

Qualifications

• 7–10 years of experience in data engineering and leading data projects.
• Strong expertise in scalable data platforms and enterprise data solutions.
• Hands-on experience with cloud-native architectures and modern data tooling.

Responsibilities

• Implement scalable data pipelines and cloud data platforms.
• Design and optimize ETL/ELT workflows.
• Develop data models and data warehouse solutions.
• Implement data processing frameworks.
• Troubleshoot data platform issues and support production pipelines.
• Manage data engineering initiatives end-to-end from architecture to deployment and optimization.

Skills

Python

SQL

Apache Spark

PySpark

Databricks

Snowflake

Cloud platforms

ETL/ELT pipelines

Data warehousing

Data modelling

Kafka

Airflow

Docker

Kubernetes

Cloud-native data architectures

Tools

Docker

Kubernetes

Airflow

Kafka

Job description

We are hiring a Senior Data Engineering Lead with 7–10 years of experience in designing and delivering scalable data platforms and enterprise data solutions. The ideal candidate should be technically strong in Python, SQL, Apache Spark, PySpark, Databricks, Snowflake, cloud platforms, ETL/ELT pipelines, data warehousing, and data modelling. Experience with Kafka, Airflow, Docker, Kubernetes, and cloud-native data architectures is preferred. The role requires an individual contributor who can work individually while collaborating with engineering, analytics, and business teams. Key responsibilities include the implementation of scalable data pipelines and cloud data platforms, designing and optimizing ETL/ELT workflows, developing data models and data warehouse solutions, implementing data processing frameworks, troubleshooting data platform issues, providing technical support for production pipelines, and managing data engineering initiatives end-to-end from architecture and development through deployment and optimization.

Requirements

• Data Warehousing