AWS Data Engineer

1 week ago

Delhi, India TerraGiG Full time

RoleAWS Data EngineerExperience8+ yearsLocationRemoteTime ZoneUKDuration2 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 processesProcess 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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