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Job DescriptionJob Description
Data Engineering and Solutions: The role requires the application of engineering expertise to design, construct, and maintain scalable ETL and ELT data pipelines within the AWS ecosystem. This encompasses cleaning, transforming, and ingesting data from disparate sources, including third-party APIs, to ensure data accuracy and readiness for analysis. The incumbent will be responsible for the development, scheduling, and monitoring of intricate workflows. Furthermore, the position involves developing scalable data solutions that fulfill client and stakeholder requirements, frequently necessitating the definition of pipeline-as-code and configurations utilizing YAML.
Data Analysis and Reporting: The individual will lead complex data analysis projects, employing Core SQL (including query services such as AWS Athena) and Python to extract, manipulate, and analyze substantial datasets sourced from locations such as S3. A key responsibility is the development and automation of reports and dashboards to furnish clients and stakeholders with critical insights.
QualificationsQualifications
- A Bachelor of Technology degree in Computer Science is preferred, coupled with a minimum of five years of experience in a data-focused role.
- Expert proficiency in SQL is required for data querying and manipulation; experience with AWS Athena is highly preferred.
- Having SDLC and programming principles approach
- Advanced proficiency in Python or Java is necessary for data analysis, scripting, automation, and the construction/consumption of APIs.
- Strong experience with the AWS cloud stack is requisite, particularly with S3, Athena, and other pertinent services (e.g., Glue, Lambda).
- Experience with cloud platforms (e.g., AWS, Azure, Google Cloud).
- Experience with test-driven development (TDD) and automated testing frameworks.
- Experience with data modeling and the construction of scalable ETL/ELT data pipelines
- Big Data background is highly preferred
Preferred
- Experience with distributed data processing frameworks within Spark.
- [Highly Desirable] Robust experience with Git-based version control systems, notably GitLab, for code management and CI/CD.
- Familiarity with containerization technologies (e.g., Docker, Kubernetes).
- Knowledge of CI/CD tools and practices.
- Familiarity with configuration languages such as YAML.
- Proven experience in data analytics, including statistical analysis and reporting.
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