
Senior Data Engineer
2 days ago
We are seeking an experienced and highly skilled Senior Data Engineer to join our dynamic team. The ideal candidate will have a strong background in building and optimizing large-scale data pipelines, architecting cloud-based data solutions, and managing complex data environments using cloud technologies. You will work closely with cross-functional teams to design, develop, and deploy data solutions that power business insights.
Key Responsibilities:
- Data Pipeline Development: Design, build, and maintain scalable ETL/ELT pipelines using AWS services such as Glue, EMR, and Athena. Leverage AWS Step Functions to automate complex workflows.
- 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.
- 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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