Data Engineer - Spark/Hadoop

PANMACH


Date: 1 day ago
City: Indore, Madhya Pradesh
Contract type: Full time
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)

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