Data Engineer - ETL/PySpark

Forward Eye Technologies

Pune District

On-site

INR 900,000 - 1,300,000

Full time

4 days ago
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Job summary

Forward Eye Technologies is seeking a senior Data Engineer to develop and optimize data pipelines, write complex SQL for analytics, and implement scalable ETL/ELT processes using PySpark/Spark with Scala. The role emphasizes cloud-native architectures and CI/CD for reliable delivery.

The ideal candidate will have 5+ years in data engineering, hands-on experience with Airflow, Kafka, and Snowflake, and be able to work across data lakes and warehouses to enable real-time analytics.

Qualifications

  • 5+ years of relevant experience in data engineering.
  • Proficient with data modeling and cloud-based data solutions.
  • Experience with Airflow, Kafka, Hive, EMR, Databricks, Snowflake.

Responsibilities

  • Write medium to complex SQL queries for data extraction and analysis.
  • Develop, test, and deploy data processing apps using PySpark/Spark with Scala.
  • Design and maintain ETL/ELT data pipelines for scalable data processing.
  • Leverage cloud platforms (AWS, Azure, Google Cloud) for scalable data solutions.
  • Implement and manage CI/CD pipelines for automated testing and deployment.

Skills

Big data
Analytical thinking
Problem-solving
Independent work

Education

Bachelor's degree
Master's degree

Tools

PySpark/Spark with Scala
Airflow
Kafka
Snowflake
Hive
Databricks
EMR

Job description

Job Responsibilities :
SQL Development :
  • - Write medium to complex SQL queries to support data extraction, transformation, and analysis.
  • - Optimize SQL queries for performance and maintainability.PySpark/Spark Development :
  • - Develop, test, and deploy data processing applications using PySpark or Spark with Scala.
  • - Implement and maintain ETL/ELT data pipelines, ensuring efficient data processing and integration.ETL/ Data Engineering Pipeline Design :
Cloud Technology Utilization :
  • - Leverage cloud platforms (AWS, Azure, Google Cloud, etc.) to build scalable and efficient data solutions.
  • - Work with cloud
  • -based data storage solutions (e.g., S3, Google Cloud Storage) and compute environments.
Debugging and Issue Resolution :
  • - Debug data processing issues and resolve challenges independently as an individual contributor.
  • - Troubleshoot and optimize existing pipelines to improve reliability and performance.Continuous Integration and Continuous Deployment (CI/CD) :
Continuous Integration and Continuous Deployment (CI/CD) :
  • - Implement and manage CI/CD pipelines for automated testing, deployment, and monitoring.
  • - Ensure code quality and best practices through version control (e.g., Git) and CI/CD tools.
Desired Skills :
Data Modeling :
  • - Design and maintain logical and physical data models to support business requirements.
  • - Ensure data models are optimized for performance, scalability, and ease of use.Airflow :
Airflow :
  • - Use Apache Airflow to orchestrate and schedule complex data workflows.
  • - Develop and maintain DAGs for task automation and monitoring.
Kafka :
  • - Utilize Apache Kafka for building real-time data streaming pipelines.
  • - Integrate Kafka with other systems for event-driven data processing.Big Data Technologies :
Big Data Technologies :
  • - Experience with big data processing frameworks such as Hive, EMR, and Databricks.
  • - Familiarity with data storage solutions like Snowflake for analytics and reporting.Data Lakes and Data Warehousing :
Data Lakes and Data Warehousing :
  • - Work with data lake solutions and data warehouses for storing and managing large datasets.
  • - Implement data lake architectures for scalable data ingestion and processing.
Technical Knowledge and Skills Required :
  • - Strong hands-on experience with PySpark or Spark with Scala for big data processing.
  • - Proficient in writing complex SQL queries and optimizing them for performance.
  • - Understanding of ETL/ELT design principles and best practices.
  • - Basic to intermediate knowledge of CI/CD processes and tools.
  • - Familiarity with cloud platforms (AWS, Azure, Google Cloud) and their data -related services.
  • - Ability to work independently and resolve issues effectively.
Soft Skills Required :
  • - Strong analytical and problem‑solving skills.
  • - Excellent communication and collaboration abilities.
  • - Ability to manage multiple tasks and projects efficiently.
  • - A proactive attitude towards learning new technologies and improving existing skills.
Work Experience :
  • - 5+ years of relevant experience in data engineering, focusing on big data processing and cloud technologies.
  • - Experience working with data engineering tools and frameworks like Airflow, Kafka, Hive, EMR, Databricks, and Snowflake.Education :
Education :
  • - Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field.
  • - A Master's degree is a plus.
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