▷ Apply Now: AWS Data Engineer

3 weeks ago

India TerraGiG Full time

Role AWS Data Engineer Experience 8+ years Location Remote Time Zone UK Duration 2 months (Extendable) Job Description - Design, development, and implementation of performant ETL pipelines using python API (pySpark) of Apache Spark on AWS EMR. - Writing reusable, testable, and efficient code - Integration of data storage solutions in spark – especially with AWS S3 object storage. Performance tuning of pySpark scripts. - Need to ensure overall build delivery quality is good and on-time delivery is done at all times. - Should be able to handle meetings with customers with ease. - Need to have excellent communication skills to interact with the customer. - Be a team player and willing to work in an onsite-offshore model, mentor other folks in the team (onsite as well as offshore) *5+ years of experience in programming with python. Strong proficiency in python *Familiarity with functional programming concepts *3+ years of hands-on experience in developing ETL data pipelines using pySpark on AWS EMR *Experience in building pipelines and data lake for large enterprises on AWS *Good understanding of Spark’s Dataframe and API *Experience in configuring EMR clusters on AWS *Experience in dealing with AWS S3 object storage from Spark. *Experience in troubleshooting spark jobs. Knowledge of monitoring spark jobs using Spark UI *Performance tuning of Spark jobs. *Understanding fundamental design principles behind business processes Process Knowledge and Expertise: - Demonstrated experience in change management processes, including understanding of governance frameworks and preparation of supporting artefacts required for approvals. - Strong clarity on the path to production, with hands-on involvement in deployments, testing cycles, and obtaining business sign-offs. - Proven track record in technical solution design, with the ability to provide architectural guidance and support implementation strategies. Databricks-Specific Skills: - Experience in at least developing and delivering end-to-end Proof of Concept (POC) solutions covering the below: - Basic proficiency in Databricks, including creating jobs and configuring clusters. - Exposure to connecting external data sources (e.g., Amazon S3) to Databricks. - Understanding of Unity Catalog and its role in data governance. - Familiarity with notebook orchestration and implementing modular code structures to enhance scalability and maintainability. Important Pointers: - Candidates must have actual hands-on work experience, not just home projects or academic exercises. - Profiles should clearly state how much experience they have in each skill area, as this helps streamline the interview process. - Candidates must know their CV/profile inside out, including all projects and responsibilities listed. Any ambiguity or lack of clarity on the candidate’s part can lead to immediate rejection, as we value accuracy and ownership. - They should be able to confidently explain their past experience, challenges handled, and technical contributions.

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