Senior Cloud Data Architect

2 weeks ago

Bengaluru, Karnataka, India beBeeDataEngineer Full time ₹ 5,00,000 - ₹ 8,00,000
Job Overview

This is a senior data engineering role that involves designing and implementing scalable data pipelines, managing cloud data infrastructure, and developing highly performant data transformation processes. The ideal candidate will have hands-on experience in building, maintaining, and optimizing data pipelines, as well as expertise in AWS services such as S3, Glue, Lambda, Redshift, EMR, and Apache Spark.

Key Responsibilities
  • Data Pipeline Design & Architecture: Design, architect, build, and optimize high-throughput ETL pipelines using AWS Glue, Lambda, and EMR to handle large datasets and complex data workflows.
  • Cloud Data Infrastructure Management: Implement, monitor, and maintain a cloud-native data infrastructure using AWS services like S3 for data storage, Redshift for data warehousing, and EMR for big data processing.
  • Data Transformation & Processing: Develop highly performant data transformation processes using Apache Spark on EMR for distributed data processing and parallel computation.
  • Real-time Data Streaming Solutions: Design and implement real-time data ingestion and streaming systems using AWS Kinesis or Apache Kafka to handle event-driven architectures, process continuous data streams, and support real-time analytics.
  • Orchestration & Automation: Use Apache Airflow to schedule and orchestrate complex ETL workflows. Automate data pipeline processes, ensuring reliability, data integrity, and ease of monitoring.
Required Skills and Qualifications
  • ETL Expertise: Solid understanding of ETL/ELT processes and experience with tools like AWS Glue for building serverless ETL pipelines.
  • AWS Services: Deep experience working with AWS cloud services, including S3, Glue, Lambda, Redshift, EMR, and Apache Spark.
  • Big Data Technologies: Expertise in using Apache Spark for distributed data processing at scale.
  • Programming & Scripting: Proficiency in Python programming language for building custom data pipelines and Spark jobs.
  • SQL & Query Optimization: Advanced knowledge of SQL and experience in query optimization, partitioning, and indexing for working with large datasets in Redshift and other data platforms.
Benefits

The successful candidate will enjoy a competitive salary and benefits package, as well as opportunities for professional growth and development.

Others

We are an equal opportunities employer and welcome applications from all qualified candidates.

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