Senior Data Engineer

Job description

• 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