Data Engineer - SQL/PySpark

Forward Eye Technologies

Dadri

On-site

INR 1,200,000 - 1,800,000

Full time

4 days ago
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Job summary

Forward Eye Technologies is seeking a seasoned Data Engineer to design and optimize data processing pipelines. You will write medium-complexity SQL queries, develop PySpark-based ETL jobs, and collaborate to translate data requirements into scalable solutions.

Responsibilities include building scalable data pipelines, implementing cloud-based storage and processing across AWS/Azure/GCP, and ensuring reliability through monitoring and CI/CD integration.

Qualifications

  • 5+ years of experience in data engineering.
  • Bachelor's degree in CS/IT or related field.
  • Hands-on SQL, PySpark, and ETL experience.
  • Experience with cloud data platforms (AWS/Azure/GCP).
  • Familiarity with CI/CD practices for data projects.

Responsibilities

  • Write medium-complexity SQL queries to extract, transform, and load data efficiently.
  • Develop and maintain data processing scripts using PySpark or Spark with Scala.
  • Design and implement ETL/data engineering pipelines to support BI and analytics needs.
  • Work with cloud platforms (AWS, Azure, GCP) to build and manage data solutions.
  • Identify, diagnose, and resolve data-related issues; monitor pipelines for reliability.
  • Implement and maintain CI/CD processes for data engineering projects.

Skills

SQL queries
PySpark / Spark
ETL design
CI/CD for data projects
Cloud platforms
Data modeling
Problem-solving
Communication

Education

Bachelor's degree in Computer Science/IT

Tools

Airflow
Kafka
AWS EMR / Databricks
Snowflake
Hive

Job description

Key Responsibilities :
SQL Development :
  • - Write medium-complexity SQL queries to extract, transform, and load data efficiently.
  • - Optimize SQL queries for performance and scalability.
  • - Collaborate with team members to understand data requirements and translate them into actionable SQL scripts.
PySpark/Spark Development :
  • - Develop and maintain data processing scripts using PySpark or Spark with Scala.
  • - Implement data transformation and ETL processes using Spark to handle large-scale data.
  • - Optimize Spark jobs for performance and troubleshoot any issues that arise during processing.
Data Engineering Pipeline Design :
  • - Design and implement ETL/data engineering pipelines to support business intelligence and analytics needs.
  • - Ensure data pipelines are scalable, reliable, and maintainable.
  • - Collaborate with the team to understand data flow requirements and implement appropriate solutions.
Cloud Technology Implementation :
  • - Work with various cloud platforms (AWS, Azure, GCP) to build and manage data solutions.
  • - Implement cloud-based data storage and processing solutions, ensuring security and compliance.
  • - Utilize cloud services for data integration, orchestration, and processing.
Issue Resolution and Debugging :
  • - Identify, diagnose, and resolve data-related issues and bugs independently.
  • - Perform root cause analysis and implement fixes for any data discrepancies or processing failures.
  • - Monitor data pipelines and systems to ensure continuous availability and reliability.
CI/CD Integration :
  • - Implement and maintain basic to intermediate level CI/CD processes for data engineering projects.
  • - Collaborate with DevOps teams to ensure smooth deployment and integration of data solutions.
  • - Automate testing and deployment processes to improve development efficiency.
Desired Skills :
Data Modeling :
  • - Experience in designing data models to support analytical and business requirements.
Airflow :
  • - Experience with Apache Airflow for workflow scheduling and orchestration.
Kafka :
  • - Knowledge of Kafka for real-time data streaming and integration.
EMR/Databricks :
  • - Experience with AWS EMR or Databricks for big data processing and analytics.
Snowflake :
  • - Familiarity with Snowflake for cloud-based data warehousing solutions.
Hive :
  • - Understanding of Hive for querying and managing large datasets.
Qualifications :
  • - Experience : 5+ years of experience in data engineering or related fields.
Technical Skills :
  • - Strong proficiency in SQL and writing medium-complexity queries.
  • - Hands-on experience with PySpark or Spark with Scala.
  • - Understanding of ETL processes and data engineering pipeline design.
  • - Basic to intermediate knowledge of CI/CD processes.
  • - Experience with cloud technologies (AWS, Azure, GCP).
Problem-Solving :
  • - Ability to troubleshoot and resolve data issues independently.
Communication :
  • - Strong verbal and written communication skills, with the ability to collaborate effectively with technical and non-technical stakeholders.
Education :
  • - Bachelor's degree in Computer Science, Information Technology, or related field.
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