Data Engineer

Fship; Dadri; On-site; INR 1,200,000 - 1,500,000; Full time

Job summary

Fship in Noida, Sector 63, is seeking a Data Engineer with 4–5 years of experience to design scalable data pipelines, data warehousing, and real-time/batch processing using the Azure ecosystem.

You will work on ETL/ELT, batch and streaming pipelines, and implement data models like Star Schema and Snowflake Schema, utilizing Azure Data Factory, Databricks, Synapse Analytics, and related tools. Proficiency in Python, SQL, Spark, and DevOps practices is expected.

Qualifications

• 4–5 years of hands-on data engineering experience.
• Strong ability to build scalable data pipelines and data warehousing solutions.
• Experience with Azure data services and real-time/batch processing.

Responsibilities

• Design and maintain ETL/ELT, batch and streaming data pipelines.
• Develop solutions using Azure Data Factory, Databricks, Event Hub, and Synapse Analytics.
• Work with SQL Server, PostgreSQL, and Cosmos DB.
• Develop data solutions using Python, SQL, and PySpark/Spark.
• Implement messaging and streaming using Kafka, Service Bus, and Queue Storage.
• Design data models using Star Schema, Snowflake Schema, and SCD.
• Implement Git, Docker, and CI/CD for deployment and version control.
• Ensure data quality, performance, reliability, and security.

Skills

ETL/ELT

Data Pipelines

Streaming

Batch Processing

Data Warehousing

Python

SQL

Spark/PySpark

Tools

Azure Data Factory

Databricks

Event Hub

Azure Storage

Synapse Analytics

SQL Server

PostgreSQL

Cosmos DB

Kafka

Azure Service Bus

Azure Queue Storage

Git

Docker

CI/CD

PySpark

Job description

We are looking for a skilled Data Engineer with 4–5 years of experience in building scalable data pipelines, data warehousing, and real-time/batch data processing solutions, with strong expertise in the Azure ecosystem.

Experience: 4–5 Years

Location: Noida, Sector 63 | Employment Type: Full-time

Key Responsibilities

• Design and maintain ETL/ELT, batch, streaming, and data pipelines.
• Develop solutions using Azure Data Factory, Databricks, Event Hub, Azure Storage, and Synapse Analytics.
• Work with SQL Server, PostgreSQL, and Cosmos DB.
• Develop data solutions using Python, SQL, and PySpark/Spark.
• Implement messaging and streaming using Kafka, Azure Service Bus, and Azure Queue Storage.
• Design data models using Star Schema, Snowflake Schema, and SCD.
• Implement Git, Docker, and CI/CD for deployment and version control.
• Ensure data quality, performance, reliability, and security.

Required Skills

Data Engineering: ETL/ELT, Data Pipelines, Streaming, Batch Processing, Data Warehousing

Programming: Python, SQL, Spark/PySpark

Data Modeling: Star Schema, Snowflake Schema, SCD

DevOps: Git, Docker, CI/CD