Leader IT Private Limited
We’re looking for a
Data Warehouse Engineer (Junior/Mid-Level)
to help design, develop, and maintain a modern data warehouse environment. You’ll work on ingesting data from multiple sources, transforming it into analytics-ready models, and ensuring high performance, reliability, and data quality. This role sits at the intersection of data engineering and analytics, with a strong focus on warehouse best practices. Key Responsibilities
Data Warehouse Development Build and maintain ETL/ELT processes to load data into the warehouse from various internal/external sources Develop and manage warehouse schemas, tables, and views to support analytics and reporting Implement data quality checks, validation, and lineage tracking Data Modeling & Performance Tuning Design efficient star/snowflake schemas for reporting and BI tools Write optimized SQL for data transformations and queries Monitor and tune warehouse performance (partitioning, indexing, clustering) Automation & Orchestration Use workflow/orchestration tools (Airflow, Prefect, dbt, Dagster or similar) to automate warehouse pipelines Develop reusable Python scripts/libraries for data transformations Work closely with analysts, BI developers and data scientists to understand data needs Provide analytics-ready datasets and documentation Support troubleshooting and resolve data issues in the warehouse Required Qualifications
Technical Skills 2–4 years of experience in data engineering or data warehouse development Strong SQL skills; experience with relational databases and data warehousing concepts Proficiency in Python for ETL/ELT and data processing (pandas, PySpark or similar) Familiarity with data modeling (star/snowflake, dimensional modeling) Exposure to at least one modern cloud data warehouse (Snowflake, BigQuery, Redshift, Synapse, etc.) Basic understanding of cloud services (AWS/GCP/Azure) Soft Skills Good problem-solving and analytical thinking Ability to write clear documentation for data models and pipelines Effective communication with both technical and non-technical stakeholders Eagerness to learn and improve warehouse best practices Skills Required
Python, SQL, Cloud Platforms, Data modeling, Data Warehouse Engineering, ETL/ELT, Dimensional Modeling, Cloud Data Warehouses, Snowflake, BigQuery, Redshift, Synapse, Workflow Orchestration, Airflow, Analytics, Agile Software Development
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Data Warehouse Engineer (Junior/Mid-Level)
to help design, develop, and maintain a modern data warehouse environment. You’ll work on ingesting data from multiple sources, transforming it into analytics-ready models, and ensuring high performance, reliability, and data quality. This role sits at the intersection of data engineering and analytics, with a strong focus on warehouse best practices. Key Responsibilities
Data Warehouse Development Build and maintain ETL/ELT processes to load data into the warehouse from various internal/external sources Develop and manage warehouse schemas, tables, and views to support analytics and reporting Implement data quality checks, validation, and lineage tracking Data Modeling & Performance Tuning Design efficient star/snowflake schemas for reporting and BI tools Write optimized SQL for data transformations and queries Monitor and tune warehouse performance (partitioning, indexing, clustering) Automation & Orchestration Use workflow/orchestration tools (Airflow, Prefect, dbt, Dagster or similar) to automate warehouse pipelines Develop reusable Python scripts/libraries for data transformations Work closely with analysts, BI developers and data scientists to understand data needs Provide analytics-ready datasets and documentation Support troubleshooting and resolve data issues in the warehouse Required Qualifications
Technical Skills 2–4 years of experience in data engineering or data warehouse development Strong SQL skills; experience with relational databases and data warehousing concepts Proficiency in Python for ETL/ELT and data processing (pandas, PySpark or similar) Familiarity with data modeling (star/snowflake, dimensional modeling) Exposure to at least one modern cloud data warehouse (Snowflake, BigQuery, Redshift, Synapse, etc.) Basic understanding of cloud services (AWS/GCP/Azure) Soft Skills Good problem-solving and analytical thinking Ability to write clear documentation for data models and pipelines Effective communication with both technical and non-technical stakeholders Eagerness to learn and improve warehouse best practices Skills Required
Python, SQL, Cloud Platforms, Data modeling, Data Warehouse Engineering, ETL/ELT, Dimensional Modeling, Cloud Data Warehouses, Snowflake, BigQuery, Redshift, Synapse, Workflow Orchestration, Airflow, Analytics, Agile Software Development
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