Data Engineer

Prasanz; Hyderabad; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

Prasanz is seeking a Data Engineer in Hyderabad to design, deploy, and monitor data pipelines, ensuring clean data for engineering teams.

You will orchestrate ETL/ELT workflows, model data warehouses in Snowflake, and maintain pipelines using Spark, Airflow, and dbt.

Qualifications

• 4+ years of experience in a Data Engineering or Data Platform role.
• Mastery of SQL design, optimization, indexing, and warehouse partitioning.
• Hands-on experience building pipelines with Apache Spark, Airflow, and dbt.
• Cloud data warehouses experience (Snowflake, AWS Redshift, or BigQuery).
• Experience writing clean, modular Python pipelines following software engineering standards.

Responsibilities

• Design and scale distributed data pipelines using Python, Spark, and SQL.
• Model data warehouse structures in Snowflake, maintaining star schemas and analytical indices.
• Orchestrate complex pipeline dependencies using Airflow and transform data with dbt.
• Build pipelines to ingest structured, semi-structured, and streaming payloads.
• Implement data validation layers, monitoring schema changes and database errors.

Skills

Python

Apache Spark

SQL

Apache Airflow

dbt

Snowflake

AWS Redshift

Google BigQuery

Tools

Airflow

dbt

Snowflake

AWS Redshift

BigQuery

Python

Spark

SQL

Job description

Back to Open Positions Data & AI Data Engineer Full-Time Hyderabad, India (Offshore) Posted 6/23/2026 Primary Technology Stack Python Apache Spark Snowflake SQL Apache Airflow dbt AWS

About The Role

We are hiring a Data Engineer to design, deploy, and monitor our data pipeline systems. You will orchestrate reliable ETL/ELT workflows, manage data warehouse schemas, and ensure engineering teams have access to clean transactional data.

Key Responsibilities

• Design and scale distributed data pipelines using Python, Apache Spark, and SQL.
• Model data warehouse structures in Snowflake, maintaining star-schemas and analytical indices.
• Orchestrate complex pipeline dependencies using Apache Airflow and transform data using dbt.
• Build pipelines to ingest structured, semi-structured, and streaming payloads.
• Implement data validation layers, monitoring schema changes and database errors.

Required Qualifications

• 4+ years of experience in a dedicated Data Engineering or Data Platform role.
• Mastery of SQL query design, database optimization, indexing, and warehouse partitioning.
• Hands-on experience building pipelines with Apache Spark, Airflow, and dbt.
• Solid experience working with cloud data warehouses (Snowflake, AWS Redshift, or Google BigQuery).
• Experience writing clean, modular Python pipelines following software engineering standards.