Algotale is a technology-driven organization focused on building scalable data solutions, cloud-native architectures, and advanced analytics platforms. We help businesses transform data into actionable insights through modern data engineering practices.
Role Overview
We are looking for a skilled Data Engineer with solid expertise in AWS/GCP, SQL, and PySpark to design, build, and optimize scalable data pipelines and cloud-based data platforms. The ideal candidate should have hands-on experience in distributed data processing and cloud environments.
Key Responsibilities
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Design, develop, and maintain scalable ETL/ELT pipelines
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Build and optimize data architectures on AWS and/or GCP
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Develop data processing frameworks using PySpark
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Write complex and optimized SQL queries for large datasets
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Work with structured and unstructured data from multiple sources
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Implement data quality, validation, and governance frameworks
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Collaborate with data analysts, data scientists, and cross-functional teams
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Monitor and troubleshoot production data systems
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Ensure best practices in performance tuning and cost optimization in cloud environments
Required Skills & Qualifications
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3+ years of experience in Data Engineering
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Strong hands-on experience with AWS (S3, Redshift, Glue, EMR, Lambda) or GCP (BigQuery, Dataflow, Cloud Storage, Dataproc)
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Strong proficiency in SQL
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Hands-on experience with PySpark
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Experience with data warehousing concepts and dimensional modeling
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Familiarity with workflow orchestration tools (e.g., Airflow)
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Understanding of distributed data processing systems
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Experience with version control tools like Git
Good to Have
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Experience with real-time data processing (Kafka or similar tools)
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Knowledge of CI/CD pipelines
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Exposure to Infrastructure as Code (Terraform, CloudFormation)