Cloudera DWH Analyst / Data Warehouse Engineer

DIXP; Delhi; On-site; INR 1,400,000 - 2,400,000; Full time

Job summary

Dixpai seeks a Cloudera DWH Analyst / Data Warehouse Engineer in Delhi to design and build data warehouses on CDP using Hive and Spark, implementing Medallion Architecture and scalable ETL/ELT pipelines.

You will optimize SQL queries, integrate data from multiple sources, and collaborate with engineers, architects, and analysts to deliver analytics-ready datasets while upholding data governance practices.

Qualifications

• 4-7 years in Data Warehousing and Big Data environments.
• Hands-on CDP, Hive, and Spark experience.
• Strong SQL development and query optimization skills.
• Experience building data pipelines and ETL workflows.

Responsibilities

• Design and implement Data Warehouse solutions on CDP using Medallion Architecture.
• Develop and optimize Hive and Spark pipelines and ETL/ELT workflows.
• Integrate data from multiple sources and ensure data quality.
• Tune Hive tables and Spark jobs for performance and scalability.
• Document data models, pipelines, and governance practices.

Skills

Big data warehousing concepts

Data modeling

SQL optimization

ETL/ELT design

Distributed data processing

Data governance awareness

Education

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

Tools

Cloudera Data Platform (CDP)

Hive

Spark

SQL

Airflow

Impala

Ranger

Atlas

Job description

Cloudera DWH Analyst / Data Warehouse Engineer

Experience: 4 - 7 yrs

Job Type: Full-Time / Contract

Education:

• UG: B.Tech/B.E. in Computer Science, Data Engineering, Information Technology, or a related field

Job Description

Project Role Description: We are looking for a Cloudera DWH Analyst with strong experience in building Data Warehouses on Cloudera Data Platform (CDP) using Hive and Spark. The candidate will be responsible for designing and implementing data warehouse layers using Medallion Architecture (Bronze, Silver, Gold) and building scalable data pipelines and transformation workflows. The role requires hands‑on expertise in Hive, Spark, SQL, and big data warehousing concepts, along with experience working in distributed data platforms.

Key Responsibilities:

Data Warehouse Design

• Design and implement Data Warehouse solutions on Cloudera Data Platform (CDP).
• Build data warehouse layers using Medallion Architecture (Bronze, Silver, Gold layers).
• Design data models and schema structures for analytics and reporting.
• Develop and manage data ingestion and transformation pipelines using Apache Spark and Hive.
• Implement ETL/ELT workflows to move data from source systems into the data warehouse layers.
• Ensure efficient data processing and transformation for analytics workloads.

SQL Development & Data Processing

• Write and optimize complex SQL queries on large datasets.
• Develop Hive queries and Spark jobs for batch data processing.
• Optimize queries and storage structures for performance and scalability.

Data Integration

• Integrate data from multiple sources such as databases, files, APIs, and enterprise systems.
• Implement data cleansing, transformation, and validation processes.

Performance Optimization

• Optimize Hive tables, partitioning strategies, and storage formats.
• Improve performance of Spark jobs and distributed data processing tasks.
• Work closely with data engineers, architects, analysts, and business stakeholders.
• Document data models, pipeline designs, and transformation logic.
• Ensure adherence to data governance and best practices.

Qualifications:

• Bachelor's degree in Computer Science, Data Engineering, Information Technology, or related field.
• 4-7 years of experience in Data Warehousing and Big Data environments.

Required Skills:

• Strong experience with Cloudera Data Platform (CDP).
• Hands‑on experience with Hive and Spark.
• Strong SQL development and query optimization skills.
• Experience building data pipelines and ETL workflows.
• Understanding of distributed data processing and big data concepts.

Preferred Skills:

• Experience with Airflow or other workflow orchestration tools.
• Familiarity with Impala for high-performance querying.
• Experience with data governance tools such as Ranger and Atlas.
• Knowledge of data lakehouse architectures and analytics platforms.