AWS Data Engineer
Job Summary:
We are seeking a skilled AWS Data Engineer with 6-8 years of experience to
enhance our data infrastructure and manage large data sets. This role will be
pivotal in developing and optimizing data pipelines and ensuring seamless
integration of data sources within our AWS cloud environment.
Key Responsibilities:
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Design and implement scalable ETL processes using AWS Glue to transform and
load data into data lakes.
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Utilize AWS S3 for data storage solutions that support a wide range of
analytics workloads.
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Develop Python and PySpark scripts to automate data processing and enrich
analytics capabilities.
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Implement and manage AWS Lambda functions for serverless computing tasks
within data workflows.
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Leverage Amazon EventBridge to handle real-time data streaming and
event-driven architecture.
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Collaborate with data analysts and business stakeholders to understand data
requirements and build robust data models.
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Optimize data query performance using Amazon Athena and ensure data
governance across all datasets.
Requirements:
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Bachelor's degree in Computer Science, Information Technology, or a related
field.
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6-8 years of experience in data engineering, specifically within the AWS
environment.
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Proficient in Python and PySpark for data manipulation and ETL processes.
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Strong SQL skills with experience in data querying and analytical functions.
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Hands-on experience with AWS services including S3, Glue, Lambda, and
Athena.
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Familiarity with data modeling principles and data governance best
practices.
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Excellent problem-solving skills and the ability to work collaboratively in
a team environment.
Preferred Qualifications:
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Experience with AWS Step Functions for orchestrating complex workflows.
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Knowledge of data warehousing concepts and experience with Amazon Redshift.
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Familiarity with containerization technologies such as Docker and
Kubernetes.
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Experience in agile development methodologies and version control systems.
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Certifications in AWS Data Engineering or relevant fields are a plus.