Data Manager

Rysun Labs; Pune District, Ahmedabad District; On-site; INR 2,800,000 - 5,200,000; Full time

Job summary

Rysun Labs in Pune invites an experienced Data Manager to lead enterprise-scale data platforms on Azure. You will shape data architecture, build ETL/ELT pipelines, and drive modernization of data platforms using ADF, Databricks, ADLS, and Synapse.

You will mentor data engineers, collaborate with stakeholders, ensure data governance, security, and cost efficiency, and deliver scalable, reliable data solutions.

Qualifications

• Experience designing enterprise-scale data platforms on cloud.
• Strong SQL and Python/PySpark skills.
• Leadership of data engineering teams and delivery timelines.

Responsibilities

• Lead design and implementation of scalable data architecture, data lakes, data warehouses, and enterprise data platforms.
• Manage end-to-end data engineering initiatives: ingestion, transformation, processing, storage, and consumption.
• Design and optimize ETL/ELT pipelines for batch and distributed processing.
• Lead data platform development using Azure Data Factory, Databricks, ADLS, and Synapse.

Skills

Big Data technologies

Distributed data processing

ETL / ELT

Data ingestion

Data Lakes

Data Warehouses

Data Architecture

Data Modelling

Batch processing

Tools

Azure Data Factory

Azure Databricks

Azure Data Lake Storage

Azure Synapse Analytics

Job description

Role Overview

We are looking for an experienced Data Manager to lead the design, development, and management of enterprise-scale data platforms. The role will be responsible for managing data architecture, data engineering initiatives, cloud data platforms, ETL/ELT pipelines, and distributed data processing solutions using Microsoft Azure technologies.

Key Responsibilities

• Lead the design and implementation of scalable data architecture, data lakes, data warehouses, and enterprise data platforms.


• Manage end-to-end data engineering initiatives covering data ingestion, transformation, processing, storage, and consumption.


• Design and optimize ETL/ELT pipelines for batch and distributed data processing.


• Lead data platform development using Azure Data Factory, Azure Databricks, ADLS, and Azure Synapse Analytics.


• Define data integration and processing strategies across structured and unstructured data sources.


• Ensure data platforms are scalable, reliable, secure, and optimized for performance and cost.


• Manage and mentor data engineering teams and provide technical guidance on data solutions.


• Collaborate with business stakeholders, architects, and technology teams to understand requirements and translate them into scalable data solutions.


• Monitor data pipelines and troubleshoot performance, data quality, and operational issues.


• Establish best practices around data governance, data quality, security, and platform standards.


• Drive modernization and migration of existing data platforms to Azure cloud-based solutions.


• Review technical designs and ensure adherence to architecture and engineering standards.

Required Technical Skills

Big Data & Data Engineering

• Big Data technologies


• Distributed data processing


• ETL / ELT


• Data ingestion and integration


• Data Lakes


• Data Warehouses


• Data Architecture


• Data Modelling


• Batch and large-scale data processing

Microsoft Azure

• Azure Data Factory (ADF)


• Azure Databricks


• Azure Data Lake Storage (ADLS)


• Azure Synapse Analytics

Programming & Database

• Strong SQL


• Python / PySpark


• Relational and distributed databases


• Data pipeline optimization

Leadership & Management

• Lead and mentor Data Engineers and technical teams.


• Plan resources and manage delivery timelines.


• Review architecture, technical designs, and data engineering solutions.


• Coordinate with stakeholders across business and technology teams.


• Ensure successful delivery of data projects within agreed timelines and quality standards.

Preferred Experience

• Experience in Azure cloud data platform implementation.


• Enterprise-scale data migration and modernization.


• Experience designing Data Lake / Data Warehouse / Lakehouse solutions.


• Strong understanding of distributed data processing.


• Experience managing data engineering teams.


• Exposure to data governance, security, and data quality frameworks.