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Agivant Technologies India Private Limited

Data Engineer

Agivant Technologies India Private Limited Pune City Subdistrict, Maharashtra, India

IT Services and IT Consulting · 51-200 employees

20 h ago
data-engineer Mid (2-5 yrs) Full-time India
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About the role

Execute the migration, consolidation, or retirement of legacy enterprise dashboards and data pipelines based on usage telemetry. Programmatically manage metric definitions and dimensions while monitoring data health to ensure pipeline freshness.

What they look for

Hive SQL Python Airflow Tableau PowerBI Data Engineering Data Migration Data Lineage Telemetry Observability Semantic Catalogs API Presto Trino Databricks

Requirements

Requires deep technical expertise in Hive, SQL, Python, and orchestration tools like Airflow. Candidates must be proficient in tracing complex data lineage and managing massive distributed datasets.

Full description

Mission: Execute massive-scale asset rationalization, pipeline migrations, and programmatic metadata implementations using enterprise query, visualization, and telemetry tools.

Core Responsibilities:

  • Asset Rationalization: Execute the migration,

consolidation, or retirement of hundreds of legacy enterprise dashboards (Tableau, PowerBI) and data pipelines based on strict usage telemetry.

  • Programmatic Definitions: Write code that pushes metric

definitions, dimensions, and owner mapping programmatically into central semantic catalogs via APIs.

  • Data Health Enforcement: Monitor real-time observability

dashboards and resolve automated escalations regarding pipeline freshness lags or volume drops within strict SLAs.

Requirements

Tech Stack & Depth:

  • Core: Hive, Advanced SQL, Python for data manipulation,

Airflow (or similar orchestration), Tableau / Enterprise Visualization tools.

  • Depth: Hands-on querying of massive distributed datasets

(Hive/Presto/Trino) and telemetry logging. Must know how to trace complex data lineage manually through code.

Good to Have / Bonus Tech Stack:

  • Experience with Databricks workflows and PySpark optimization.
  • Integrating automated testing in dbt.
  • Utilizing AI coding assistants for rapid SQL script generation and optimization.

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