Data & Analytics Engineer

PwC India

Bengaluru

On-site

INR 1,200,000 - 1,800,000

Full time

14 days+

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Job summary

A reputable consulting firm in Bengaluru is seeking a Data Engineer with extensive experience in designing and implementing modern data architectures, including lakehouse and data mesh. The role requires 5–10 years in data engineering, preferably in industrial sectors, alongside strong skills in Python, Apache Airflow, and BI tools like Power BI, Looker, or Tableau for analytics solutions. The candidate will also collaborate with AI/ML teams to ensure data readiness for model training and inference.

Qualifications

  • 5–10 years in data engineering, preferably with industrial or manufacturing data.
  • Experience in building data transformation layers and governance frameworks.
  • Strong background in orchestration tools and BI solutions.

Responsibilities

  • Design and implement modern data architectures including lakehouse and data meshes.
  • Collaborate with AI/ML teams for ensuring data readiness.
  • Create dashboards and analytics solutions using Power BI, Looker, or Tableau.

Skills

Data architecture design
Python for data engineering
Apache Airflow
Dashboard creation with BI tools
Data quality frameworks
Data modelling

Tools

Looker
Tableau
dbt

Job description

  • Design and implement modern data architectures: lakehouse, data meshes, and streaming pipelines
  • Build transformation layers using dbt and orchestration with Airflow
  • Implement data quality frameworks and governance practices
  • Create dashboards and analytics solutions using Power BI, Looker, or Tableau
  • Design KPI frameworks and data storytelling approaches for engineering metrics
  • Collaborate with AI/ML teams to ensure data readiness for model training and inference
  • Orchestration: Apache Airflow, Dagster, Prefect
  • Python for data engineering and testing
  • BI tools: Power BI, Looker, Tableau
  • Data modelling and lakehouse architecture
Experience

5–10 years in data engineering with experience in industrial or manufacturing data environments preferred

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