Azure Data Engineer

Xoriant; Pune District, Mumbai, Bengaluru; Hybrid; INR 1,800,000 - 3,000,000; Full time

Job summary

Xoriant is seeking a Data Engineer to design, build, and operate scalable data pipelines on Microsoft Azure with Databricks (Spark/Delta). You will develop curated analytics-ready datasets for BI and enable robust data operations in an Agile environment.

The role emphasizes hands-on delivery, data quality, and cost optimization with Spark tuning. Exposure to GenAI initiatives is a strong plus for future roadmaps.

Qualifications

• 38 years of hands‑on Data Engineering experience.
• Strong experience with Azure data ecosystem and Databricks.
• Strong SQL and Python (production-grade coding).
• Orchestration experience with Azure Data Factory and/or Databricks Workflows.
• Practical experience implementing incremental processing and robust pipelines.

Responsibilities

• Build and maintain data pipelines on Azure using Databricks and Azure services.
• Develop curated, analytics-ready datasets for BI/reporting.
• Good understanding of FACT and dimensional modelling.
• Implement incremental load patterns, backfills, and late-arriving data handling.
• Ensure strong data quality, reconciliation checks, and pipeline monitoring.
• Optimize performance and cost (Spark tuning, partitioning strategies, file formats).
• Maintain documentation and support releases in an Agile model.

Skills

Data engineering

SQL

Python

Spark (PySpark)

Tools

Azure Databricks

Azure Data Factory

Delta Lake

Spark

Databricks Workflows

Job description

Role Overview

We are looking for a contract Data Engineer to support enterprise BI & Analytics deliveries within IDO. The role will design, build, and operate scalable data pipelines and curated datasets on Microsoft Azure, with strong hands‑on delivery in Databricks (Spark/Delta). Exposure to AI engineering / GenAI enablement is a strong plus for future roadmap initiatives.

Key Responsibilities

• Build and maintain data pipelines on Azure (ingestion, transformation, validation, and publishing) using Databricks and Azure services.
• Develop curated, analytics‑ready datasets for BI/reporting and downstream consumers.
• Good understanding of FACT and dimensional modelling.
• Implement incremental load patterns, backfills, and handling of late‑arriving data to minimize full reloads.
• Ensure strong data quality, reconciliation checks, and pipeline monitoring/alerting.
• Optimize performance and cost (Spark tuning, partitioning strategies, file formats).
• Maintain documentation (source-to-target mappings, runbooks) and support releases/production issues in an Agile model.

Must‑Have Skills (Azure Data Engineering + Databricks)

• 38 years of hands‑on Data Engineering experience.
• Strong experience with Azure data ecosystem and Databricks:
• Spark (PySpark), Delta Lake (MERGE/upserts, schema evolution), Lakehouse patterns
• Strong SQL and Python (production-grade coding).
• Orchestration experience with Azure Data Factory and/or Databricks Workflows.
• Practical experience implementing incremental processing and robust operational pipelines (retry, idempotency, monitoring).