Master Data Solutions Architect

4 days ago

Lahore, Punjab, Pakistan beBeeDataEngineer Full time
Senior Data Engineer

We are seeking a skilled Senior Data Engineer to develop innovative data solutions and optimize large-scale data pipelines.

Key Responsibilities:
  • Data Pipeline Development: Design, build, and maintain scalable ETL/ELT pipelines using AWS services such as Glue, EMR, and Athena.
  • Data Warehousing: Architect and manage data warehouses using cloud technologies, integrating with S3, RDS, and DynamoDB for structured (SQL) and unstructured (NoSQL) data needs.
  • Big Data Processing: Utilize PySpark on AWS EMR for distributed data processing, ensuring effective transformation of raw data into business insights.
  • Database Management: Manage both SQL (e.g., PostgreSQL, MySQL) and NoSQL (e.g., DynamoDB, MongoDB) databases, ensuring efficient storage, retrieval, and querying of data.
  • Real-Time Data Processing: Implement and maintain real-time streaming data solutions using AWS Kinesis or Kafka for low-latency data processing.
  • Cloud Monitoring & Automation: Use AWS CLI and CloudWatch to monitor, automate, and optimize data pipelines, ensuring efficient use of cloud resources.
  • Data Governance & Security: Ensure adherence to best practices for data security, governance, and compliance, including data encryption and access controls.
  • Collaboration: Work closely with data scientists, analysts, and business stakeholders to align data infrastructure with business objectives.
  • Documentation: Maintain detailed documentation of data models, data pipeline processes, and system architectures.
Requirements
  • 5+ years of experience as a Data Engineer, with a strong emphasis on cloud-based data warehousing and ETL pipelines.
  • Proficiency with AWS services including EMR, Athena, Glue, Step Functions, ElasticSearch, RDS, Redshift, DynamoDB, and S3.
  • Advanced SQL skills and experience with relational databases like PostgreSQL, MySQL as well as NoSQL databases such as MongoDB and DynamoDB.
  • Hands-on experience in Python for data processing and automation, with knowledge of AWS CLI.
  • Strong proficiency with PySpark for distributed data processing and transformation.
  • Experience with AWS CloudWatch for monitoring and optimizing data workflows.
  • Data warehouse architecture experience, including optimizing query performance in large-scale environments.
  • Strong understanding of data governance, security, and compliance best practices.
  • Bachelor's degree in Computer Science, Engineering, or a related field.

Nice to have:

  • Familiarity with real-time data streaming solutions such as Apache Kafka or AWS Kinesis.

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