JobHabor
Location
Bengaluru, Karnataka, India
Workplace
Hybrid
Employment
Full Time
Salary
Apply on the employer’s site

Posted 1mo ago

Key Responsibilities

  • Design, develop, and optimize scalable ETL/ELT pipelines for data ingestion and transformation.
  • Build and maintain robust data pipelines using AWS cloud services.
  • Partner with Business Intelligence (BI), AI/ML, and Infrastructure teams to deliver reliable and scalable data platform solutions.
  • Develop efficient SQL queries and Python scripts for data processing, automation, and analytics.
  • Create and maintain technical documentation, including solution designs, data flow diagrams, and operational guides.
  • Develop comprehensive unit tests and perform code reviews to ensure high-quality, reliable, and maintainable code.
  • Monitor, troubleshoot, and optimize data pipelines to ensure performance, scalability, and reliability.
  • Work on multiple projects simultaneously while managing priorities in a fast-paced environment.
  • Follow coding standards, best practices, and data governance guidelines.

Required Skills & Qualifications

  • 3–5 years of hands-on experience in Data Engineering.
  • Strong experience in designing and developing ETL/ELT pipelines.
  • Proficiency in SQL and Python programming.
  • Hands-on experience with AWS services, including:
  • Amazon Redshift
  • AWS Lambda
  • Amazon S3
  • AWS Glue (preferred)
  • AWS IAM
  • Amazon CloudWatch
  • Experience with workflow orchestration tools such as Apache Airflow (preferred).
  • Understanding of data warehousing concepts and dimensional data modeling.
  • Knowledge of version control systems such as Git.
  • Experience writing unit tests and following software development best practices.
  • Strong analytical, problem-solving, and debugging skills.
  • Excellent communication and documentation skills.
  • Ability to manage multiple tasks and work effectively in a collaborative environment.

Preferred Skills

  • Experience with CI/CD pipelines and DevOps practices.
  • Knowledge of Spark, PySpark, or Databricks is an advantage.
  • Exposure to AI/ML data pipelines and feature engineering.
  • Familiarity with Agile/Scrum development methodologies.
  • AWS Certification (Developer Associate or Data Engineer Associate) is a plus.

Key Competencies

  • AWS Data Engineering
  • ETL/ELT Development
  • SQL & Python
  • Amazon Redshift
  • AWS Lambda
  • Amazon S3
  • Data Warehousing
  • Unit Testing
  • Technical Documentation
  • Problem Solving
  • Team Collaboration
  • Multitasking
  • Agile Development

Educational Qualification

  • Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
  • Relevant AWS certifications will be an added advantage.

Skills

  • AWS
  • ETL
  • ELT
  • SQL
  • Python
  • Redshift
  • AWS Lambda
  • S3
  • AWS Glue
  • IAM
  • AWS CloudWatch
  • Airflow
  • Git
  • Spark
  • PySpark
  • Databricks

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