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Senior Data Engineer
1 month ago
Key Responsibilities:
- Design and Develop Data Pipelines:
- Create and maintain data pipelines using Python, PySpark, and Spark SQL.
- Build Airflow DAG pipelines for seamless data ingestion and workflow automation.
- Data Management and Processing:
- Process large datasets using PySpark and DataFrames.
- Leverage your expertise in SQL for data extraction, transformation, and loading (ETL).
- Cloud Services and Architecture:
- Implement and maintain data solutions on AWS using services like S3, Glue, Redshift, Lambda, IAM, EMR, Athena, and Spectrum.
- Ensure data security, scalability, and cost-effectiveness within the AWS environment.
- Collaboration and Support:
- Work closely with application development teams to align data engineering solutions with business requirements.
- Lead a team of engineers in project delivery.
- Performance Optimization and Monitoring:
- Conduct performance tuning and optimization of SQL queries.
- Monitor and troubleshoot issues within data pipelines.
Requirements:
- 5-6 years of experience in data engineering or related fields.
- Proven track record of leading teams of at least 4 members.
- Experience working within agile development environments, collaborating with cross-functional teams.
At Alignity Solutions, we are looking for an expert in data engineering to join our team. As a Data Engineering Lead, you will leverage your experience in designing and developing data pipelines to ensure the successful delivery of data-driven solutions. Your strong background in business intelligence (BI) and data warehousing technologies will be essential in this role.
