Data Engineer - Spark/Hadoop

5 years

0 Lacs

Posted:5 days ago| Platform: Linkedin logo

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On-site

Job Type

Full Time

Job Description

Role : Data : Jaipur/Indore Notice : Immediate joiners only Basic Responsibilities (Must-Haves) 5+ years of experience in dashboard story development, dashboard creation, and data engineering pipelines. Hands-on experience with log analytics, user engagement metrics, and product performance metrics. Ability to identify patterns, trends, and anomalies in log data to generate actionable insights for product enhancements and feature optimization. Collaborate with cross-functional teams to gather business requirements and translate them into functional and technical specifications. Manage and organize large volumes of application log data using Google Big Query. Design and develop interactive dashboards to visualize key metrics and insights using any of the tool like Tableau Power BI, or ThoughtSpot AI . Create intuitive, impactful visualizations to communicate findings to teams including customer success and leadership. Ensure data integrity, consistency, and accessibility for analytical purposes. Analyse application logs to extract metrics and statistics related to product performance, customer behaviour, and user sentiment. Work closely with product teams to understand log data generated by Python-based applications. Collaborate with stakeholders to define key performance indicators (KPIs) and success metrics. Can optimize data pipelines and storage in Big Query. Strong communication and teamwork skills. Ability to learn quickly and adapt to new technologies. Excellent problem-solving skills. Preferred Responsibilities (Nice-to-Haves) Knowledge of Generative AI (GenAI) and LLM-based solutions. Experience in designing and developing dashboards using ThoughtSpot AI. Good exposure to Google Cloud Platform (GCP). Data engineering experience with modern data warehouse architectures. Additional Responsibilities Participate in the development of proof-of-concepts (POCs) and pilot projects. Ability to articulate ideas and points of view clearly to the team. Take ownership of data analytics and data engineering solutions. Additional Nice-to-Haves Experience working with large datasets and distributed data processing tools such as Apache Spark or Hadoop. Familiarity with Agile development methodologies and version control systems like Git. Familiarity with ETL tools such as Informatica or Azure Data Factory (ref:hirist.tech) Show more Show less

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