Data Engineer

Codeforce 360; Hyderabad, Chennai District, Bengaluru; Hybrid; INR 900,000 - 1,300,000; Full time

Job summary

Codeforce 360 is seeking an experienced Data Engineer in Hyderabad to design, develop, and optimize scalable data pipelines using modern cloud data engineering technologies.

You will work with PySpark, Scala, Databricks, and Snowflake to ingest, transform, and validate data from multiple sources and build robust data models and frameworks for production use.

Qualifications

• 5+ years hands-on data engineering experience.
• Proficient in Scala, PySpark, Databricks and Snowflake.
• Experience designing scalable data pipelines and data processing.

Responsibilities

• Design, develop, and optimize scalable ETL/ELT data pipelines using PySpark and Scala.
• Develop and optimize data processing jobs using Databricks and Apache Spark.
• Build and maintain data models, tables, views, and pipelines in Snowflake.
• Ingest, transform, cleanse, and validate data from multiple sources.
• Optimize Spark jobs, SQL queries, and Snowflake workloads for performance and cost.
• Work with large-scale structured and semi-structured datasets.
• Implement data quality, monitoring, error handling, and troubleshooting processes.
• Collaborate with Data Architects, Business Analysts, and application teams.
• Develop reusable production-ready data engineering frameworks.
• Participate in code reviews, testing, deployment, and production support.

Skills

Data engineering

ETL/ELT

Cloud data pipelines

Big data

SQL

Tools

Scala

PySpark

Databricks

Snowflake

Apache Spark

Job description

We are looking for an experienced Data Engineer with 5+ years of hands‑on experience in Scala, PySpark, Databricks, and Snowflake. The candidate will be responsible for designing, developing, and optimizing scalable data pipelines and data processing solutions using modern cloud data engineering technologies.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines using PySpark and Scala.
• Develop and optimize data processing jobs using Databricks and Apache Spark.
• Build and maintain data models, tables, views, and pipelines in Snowflake.
• Perform data ingestion, transformation, cleansing, and validation from multiple sources.
• Optimize Spark jobs, SQL queries, and Snowflake workloads for performance and cost.
• Work with large-scale structured and semi-structured datasets.
• Implement data quality, monitoring, error handling, and troubleshooting processes.
• Collaborate with Data Architects, Business Analysts, and application teams to understand data requirements.
• Develop reusable and production-ready data engineering frameworks.
• Participate in code reviews, testing, deployment, and production support.
• Follow best practices for data security, governance, and pipeline reliability.