Data Engineer

Pune, Hyderabad, Maharashtra, India

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Pay: Pay not listed
Work setting: Not stated
Employment: Full-time — employment source
Employment type in the employer’s listing: Full time
From the employer’s posting

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What you’ll work on

Full posting

Migrate, consolidate, or retire legacy dashboards and pipelines based on usage telemetry
Write code that pushes metric definitions, dimensions, and owners into semantic catalogs via APIs
Monitor observability dashboards and resolve pipeline freshness or volume alerts within SLAs

From the employer’s posting

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

Write code that pushes metric definitions, dimensions, and owner mapping programmatically into central semantic catalogs via APIs.

Monitor real-time observability dashboards and resolve automated escalations regarding pipeline freshness lags or volume drops within strict SLAs.

What you’ll bring

All qualifications

Core experience

Advanced SQL and hands-on querying of massive distributed datasets (Hive, Presto, Trino)
Python for data manipulation
Airflow or similar orchestration tools
Tableau or enterprise visualization tool experience
Ability to trace complex data lineage manually through code

Qualification wording

Hands-on querying of massive distributed datasets (Hive/Presto/Trino) and telemetry logging.

Python for data manipulation

Airflow (or similar orchestration)

Tableau / Enterprise Visualization tools

Must know how to trace complex data lineage manually through code.

Tools in this posting

Python
SQL
Databricks
dbt
Hive
Power BI
Tableau
Trino
Airflow
PySpark

Source

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.

Posting record

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Status in our records: No longer listed
First seen by us: Sep 17, 2026 · 38 days ago
Recorded sightings: 11
Last seen by us: Oct 9, 2026
Employer says posted: Sep 15, 2026

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Job description

View original posting ↗

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.

Source details

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Pay

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Location & working pattern

Pune, Hyderabad, Maharashtra, India

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Open source at agivant.zohorecruit.in ↗Read the full description ↓

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