
aws data engineer
3 days ago
Job Description:
Data Engineer with experience in digital channel activities, data engineering, and cloud technologies, particularly in AWS. This is an exciting opportunity to work on a project with a focus on integrating and processing channel activity data from multiple sources, including Terradata, and Hadoop environments. The ideal candidate will possess strong knowledge of AWS, Python, and has work experience in handling data from various sources such as Hadoop , and Terradata, working on large-scale data engineering solutions for data, and knowledge of data processing architecture.
Key Responsibilities:
- Design, build, and maintain robust data pipelines for processing channel activity data, focusing on digital channels and integrating multiple sources of data such as Hadoop and Terradata.
- Work on AWS cloud infrastructure (including services like Pyspark ,Glue ,EMR ,lambda, Redshift , Athena, and other services like Iceberg) and orchestration tools like Airflow to ensure high availability, scalability, and performance.
- Leverage Python for building automated data engineering solutions and data transformations.
- Collaborate with cross-functional teams to ensure data from various digital channels is effectively ingested and processed.
- Contribute to architecture decisions related to data lakes, data warehouses, and big data ecosystems.
- Ensure data quality, governance, and integrity across all data systems.
- Engage in continuous learning and adapting of new technologies and industry best practices to improve data processes.
Skills & Experience Required:
Experience with Data Engineering: Proven experience working as a Data Engineer in greenfield environments (i.e., starting projects from scratch).
- AWS: Strong hands-on experience with AWS technologies such as Pyspark ,Glue ,EMR ,lambda, Redshift , Athena, EC2 and S3.
- Python: Proficiency in Python for data processing, automation, and pipeline development.
- Big Data Platforms: Experience with big data technologies like Hadoop and Terradata.
- Strong Analytical Skills: Ability to analyse and interpret data from different digital channels.
- Collaboration: Ability to work closely with cross-functional teams, including business analysts, data scientists, and stakeholders.
- Problem Solving: Strong problem-solving skills and ability to handle complex data-related challenges.
- Communication: Excellent communication skills, both written and verbal, for documentation and collaboration.
Desirable Qualifications:
- A degree in Computer Science, Engineering, or a related field.
- Certifications or experience in AWS Cloud or relevant data engineering tools would be beneficial.
- Experience in working on snowflake would be good to have.
- Knowledge of ingesting real time data ( Apache Kafka ) would be advantage.
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