Datawarehouse Lead

NSL Group; Telangana; On-site; INR 3,000,000 - 5,200,000; Full time

Job summary

NSL Group in Kandlakoya seeks a Data Warehouse Lead to design and build enterprise-grade data platforms including data lakes, data warehouses, and data marts to support analytics, BI, and AI across finance, operations, HR, sales, and supply chain.

The ideal candidate has strong expertise in modern data architecture, data science fundamentals, and a track record of enabling data-driven decision-making at scale across multiple business functions.

Qualifications

• Bachelors or Masters degree in CS, data engineering, IS, or related field.
• 7+ years of experience in data engineering, data architecture, or enterprise analytics roles.
• Strong expertise in data lake & warehouse technologies, ETL/ELT tools, and cloud platforms.
• Proficient in SQL, Python, Scala.
• Knowledge of Kimball/Inmon methodologies and dimensional modeling.
• Experience creating data marts for department analytics.
• Familiarity with governance, metadata management, and data security basics.

Responsibilities

• Design and implement scalable data lake and warehouse architectures.
• Develop enterprise data models, data marts, and semantic layers.
• Define data ingestion frameworks for batch and real-time pipelines.
• Architect data structures to support analytics, ML, and AI workflows.
• Ensure data quality, integrity, and consistency across systems.
• Implement metadata management, cataloging, lineage tracking, and access control.
• Optimize storage, query performance, and cost across platforms.
• Collaborate with stakeholders to translate requirements into models.
• Create department data marts for finance, HR, production, and marketing analytics.
• Enable feature stores and ML-ready datasets with data science teams.
• Lead modernization using cloud-native tech, lakehouse architectures, and data fabric.
• Advance data security and compliance practices.

Skills

Data lake & warehouse technologies

ETL/ELT Tools

Cloud Platforms

Programming

Data Modeling

Data Storage

Data science concepts

Data marts for analytics

Education

Bachelor's or Master's degree in Computer Science / Data Engineering / Information Systems

Tools

Snowflake

Redshift

Azure Synapse

Google BigQuery

Databricks

Hadoop

Informatica

Talend

dbt

Azure Data Factory

AWS Glue

Airflow

Kafka

Spark Streaming

Power BI

Looker

Job description

Job Title: Data Warehouse Lead

Department: Data & Analytics Location: Corporate Office, Kandlakoya Employment Type: Full-Time

About the Role

We are seeking a highly skilled Data Warehouse Lead to design and build enterprise-grade data platforms including data lakes, data warehouses, and data marts to support analytics, business intelligence, and AI applications across multiple business functions such as finance, operations, HR, sales, supply chain, and product management. The ideal candidate will have strong expertise in modern data architecture, data science fundamentals, and a proven track record of enabling data-driven decision-making at scale.

Key Responsibilities

Data Architecture & Engineering

• Design and implement scalable data lake and data warehouse architectures using cloud or hybrid platforms.
• Develop enterprise data models, data marts, and semantic layers to support department-specific requirements.
• Define data ingestion frameworks (batch and real-time) using ETL/ELT tools and pipelines.
• Architect data structures to support analytics, reporting, machine learning, and AI-driven workflows.

Data Governance & Optimization

• Ensure data quality, integrity, and consistency across all enterprise systems.
• Implement metadata management, data cataloging, lineage tracking, and access control.
• Optimize data storage, query performance, and cost across the data platform.

Cross-Functional Enablement

• Work with business stakeholders to convert requirements into logical and physical data models.
• Build subject-specific data marts (finance, HR, production, marketing, etc.) for performance analytics.
• Partner with data science teams to enable feature stores, ML-ready datasets, and AI model deployment pipelines.

Innovation & Automation

• Lead modernization initiatives using cloud-native technologies, lakehouse architectures, and data fabric models.
• Integrate advanced analytics and predictive intelligence capabilities into the data platform.
• Evaluate and implement best practices for data security and compliance.

Required Skills & Qualifications

• Bachelors or Masters degree in Computer Science, Data Engineering, Information Systems, or related field.
• 7+ years of experience in data engineering, data architecture, or enterprise analytics roles.
• Strong expertise in:
• Data lake & warehouse technologies: Snowflake, Redshift, Azure Synapse, Google BigQuery, Databricks, Hadoop, etc.
• ETL/ELT Tools: Informatica, Talend, dbt, Azure Data Factory, AWS Glue, etc.
• Cloud Platforms: AWS, Azure, GCP.
• Programming: SQL, Python, Scala.
• Data Modeling: Kimball/Inmon methodologies, dimensional modeling, star/snowflake schemas.
• Data Storage: Delta Lake, Parquet, ORC, Hive Metastore.
• Knowledge of data science concepts and ML workflows, including support for model training and feature engineering.
• Experience creating data marts for department-specific analytics.

Preferred / Good to Have

• Hands-on experience with lakehouse architectures (e.g., Databricks, Snowflake).
• Knowledge of Airflow, Kafka, Spark Streaming, or real-time data processing.
• Exposure to BI tools: Power BI, Tableau, Qlik, or Looker.
• Experience with governance, MDM (Master Data Management), and data security frameworks.