Chief Data Architect

3 weeks ago

Bengaluru, Karnataka, India The Metromax Group Full time

Job Summary

We are seeking a highly skilled Data Engineer to join our team at The Metromax Group. As a key member of our data engineering team, you will be responsible for designing and developing large-scale data pipelines using AWS Glue, EMR, Spark Scala, and S3.

Key Responsibilities:

  • Data Pipeline Development: Design and develop data pipelines that support both batch and real-time data processing needs.
  • ETL Process Implementation: Implement ETL processes to extract, transform, and load data from various sources into the data lake.
  • Big Data Processing: Leverage Apache Spark on EMR for big data processing and transformations, using Spark Scala.
  • Data Storage Management: Manage and optimize data storage on S3, ensuring proper data partitioning, file formats (Parquet, ORC, Avro), and lifecycle policies for cost-effective storage solutions.
  • EMR Cluster Optimization: Monitor, troubleshoot, and optimize EMR clusters for performance, scalability, and cost efficiency.
  • Collaboration: Collaborate with data architect and analysts to ensure seamless data integration and support advanced analytics and machine learning models.
  • AWS Automation: Automate data workflows using AWS Step Functions, Lambda, and other orchestration tools.

Required Qualifications:

  • Education: Bachelor's or master's degree in computer science, Data Engineering, or a related technical field.
  • Experience: 3-5 years of experience in data engineering, particularly using AWS services (EMR, Glue, S3, Lambda).
  • Skills: Strong expertise in Apache Spark for distributed data processing, with hands-on coding experience in Scala and Python. Experience with building ETL pipelines and working with big data in a cloud-based Lakehouse environment.
  • Knowledge: Deep understanding of data formats (Parquet, Avro, ORC) and file optimization techniques. Familiarity with data modeling principles, including partitioning, bucketing, and schema management in AWS Glue Data Catalog.
  • SQL and Query Optimization: Strong knowledge of SQL and query optimization for working with large datasets.
  • Security: Experience with AWS security services such as IAM, KMS (Key Management Service), and encryption best practices.
  • Troubleshooting and Performance Tuning: Proficiency in troubleshooting and performance tuning of Spark and EMR clusters for large-scale data processing.
  • CICD Pipelines and Infrastructure-as-Code: Familiarity with CI/CD pipelines and infrastructure-as-code (Terraform, CloudFormation) for managing AWS environments.

Preferred Qualifications:

  • Certification: AWS Certified Data Analytics, Developer, or Solutions Architect certification.
  • Streaming Data Technologies: Experience with streaming data technologies such as Kinesis or Kafka for real-time data ingestion.
  • Serverless Computing: Knowledge of serverless computing and experience with AWS Lambda, Step Functions, and DynamoDB.
  • DevOps and Automation Tools: Familiarity with DevOps and automation tools (e.g., Jenkins, Git, Docker).

Soft Skills:

  • Problem-Solving and Analytical Thinking: Strong problem-solving and analytical thinking skills.
  • Communication: Excellent communication skills to explain complex technical issues to both technical and non-technical stakeholders.

Salary:$120,000 - $180,000 per year.

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