Senior Data Architect

6 days ago

Lahore, Punjab, Pakistan beBee Careers Full time

We are seeking a highly skilled and experienced Senior Data Engineer to join our team. This role is responsible for designing, building, and maintaining large-scale data pipelines, architecting cloud-based data solutions, and managing complex data environments using cloud technologies.

The ideal candidate will have a strong background in data engineering, with experience in building and optimizing ETL/ELT pipelines using AWS services such as Glue, EMR, and Athena. They will also have expertise in architecting and managing data warehouses using cloud technologies, integrating with S3, RDS, and DynamoDB for both structured (SQL) and unstructured (NoSQL) data needs.

Some of the key responsibilities of this role include:

  • 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, while integrating with S3, RDS, and DynamoDB for both structured (SQL) and unstructured (NoSQL) data needs.
  • Big Data Processing: Utilize PySpark on AWS EMR for distributed data processing, ensuring the 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 data is efficiently stored, retrieved, and queried.
  • 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 and ensure 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.

To be successful in this role, you will need to have:

  • 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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