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Accolite
Job Summary:
We are seeking a skilled Data Engineer with strong hands-on experience in AWS Athena, AWS Glue, and data processing using Python / Scala / SQL.
The ideal candidate will design and develop data pipelines, build ETL workflows, manage large-scale datasets on AWS, and enable analytics and reporting across various platforms.
Key Responsibilities:
Design, build, and maintain scalable ETL/ELT pipelines using AWS Glue and Glue Jobs (Python/Scala).
Develop and optimize data queries using AWS Athena.
Work extensively with Python/Scala/SQL for data transformations and dataset enrichment.
Manage and maintain data stored in S3 and integrate with AWS services such as Lambda, Glue Catalog, and Lake Formation.
Implement data quality checks, schema validations, and metadata management.
Collaborate with analytics, data science, and engineering teams to deliver reliable datasets.
Optimize data workflows for performance, scalability, and cost efficiency.
Work with CI/CD pipelines for deploying data pipelines and scripts.
Ensure data governance, security policies, and best practices across AWS environments.
Required Qualifications:
5–7 years of experience in data engineering.
Strong hands-on experience with AWS Athena and AWS Glue.
Proficiency in Python, Scala, and SQL for data processing.
Experience working with large datasets stored on AWS S3.
Good understanding of distributed processing and data modeling concepts.
Experience with version control (Git) and CI/CD practices.
Strong analytical, debugging, and problem-solving skills.
Preferred Skills:
Experience with AWS Lambda, Glue Catalog, or Lake Formation.
Exposure to Spark, PySpark, or EMR.
Knowledge of orchestration tools (Airflow, Step Functions, etc.).
Understanding of data governance, metadata, and lineage management.
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