AWS Lead Data Engineer
Job Summary:
The AWS Lead Data Engineer will play a critical role in our data engineering
team, focusing on designing and implementing scalable data solutions on AWS.
The successful candidate will leverage advanced technologies like Snowflake
and Pyspark to drive impactful analytics, ensuring data integrity and
accessibility within the organization.
Key Responsibilities:
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Design and architect robust data pipelines on AWS to facilitate data
ingestion, transformation, and storage.
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Lead a team of data engineers, providing guidance and support to ensure
project milestones are met.
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Implement and optimize data processing workflows using Snowflake and Pyspark
for real-time analytics.
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Collaborate with cross-functional teams to gather requirements and translate
them into technical specifications.
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Ensure data security, quality, and governance while maintaining compliance
with industry standards.
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Perform regular performance tuning and system optimization to enhance data
handling capabilities.
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Mentor junior engineers and promote best practices within the team to foster
a culture of continuous improvement.
Requirements:
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Bachelor’s or Master’s degree in Computer Science, Engineering, or related
field.
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8+ years of experience in data engineering, with a focus on AWS
technologies.
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Proficiency in Snowflake and Pyspark for efficient data processing and
analytics.
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Demonstrated experience in leading teams and managing projects successfully.
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Strong understanding of data warehousing concepts and cloud architectures.
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Excellent problem-solving skills and ability to work under tight deadlines.
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Strong interpersonal skills with a collaborative mindset and a focus on
teamwork.
Preferred Qualifications:
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Experience with additional AWS services such as Redshift, DynamoDB, or EMR.
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Familiarity with machine learning frameworks and their implementation.
- Knowledge of data visualization tools such as Tableau or Power BI.
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Certifications in AWS (e.g., AWS Certified Data Analytics, AWS Certified
Solutions Architect) are a plus.