Azure Data Engineer

Metlife; Pune District; Hybrid; INR 900,000 - 1,500,000; Full time

Job summary

MetLife India in Pune is seeking a Data Engineer to design and maintain scalable data pipelines powering analytics and data products. You will work with cloud-based tools, ensure data quality, security, and performance, and collaborate with analysts and engineers.

You’ll build batch and streaming ETL processes, ingest data from internal systems and external sources, document data models, and participate in CI/CD and governance practices.

Qualifications

• Bachelor's degree in Computer Science or an equivalent field.
• Strong SQL skills including DDL/DML and window functions.
• Programming experience with Python; Java/Scala also acceptable.

Responsibilities

• Build and maintain reliable, scalable data pipelines for analytics and data products.
• Ingest data from internal systems and external sources (APIs, files, databases).
• Develop and support batch and streaming ETL/ELT pipelines.
• Ensure data quality, security, and performance; implement monitoring and alerts.
• Collaborate with analysts, product owners, and engineers to meet data needs.
• Contribute to data dictionaries, runbooks, and documentation.
• Follow CI/CD and data governance policies; participate in code reviews.
• Troubleshoot pipeline issues and assist in incident resolution.

Skills

SQL

Python

Java/Scala

Education

Bachelor of Computer Science or equivalent

Tools

Azure

Git

Terraform

Databricks

Synapse

Job description

Key Responsibilities:

• As a Data Engineer, youll help build and maintain reliable, scalable data pipelines and curated datasets that power analytics, reporting, and data products. You’ll work with modern cloud and data engineering tools, learning best practices around data quality, security, and performance.
• Assist in building and maintaining batch and/or streaming ETL/ELT pipelines.
• Develop and support data ingestion from internal systems and external sources (APIs, files, databases including structure, semi-structured or unstructured data).
• Develop notebook to transform curated data into SCV specific unified data model
• Help model and curate datasets for analytics (dimensional models, curated “gold” tables, semantic layer inputs).
• Support data quality checks, monitoring, and alerting (validation rules, reconciliation).
• Collaborate with analysts, product owners, and engineers to understand data needs and deliver datasets.
• Contribute to documentation, data dictionaries, and runbooks.
• Participate in code reviews and follow engineering standards (naming, testing, CI/CD).
• Troubleshoot pipeline failures and support incident resolution with guidance from senior engineers.
• Follow data governance and security policies (PII handling, access control, retention).

Education:

• Bachelor of Computer Science or equivalent.

Technical Stack:

• SQL (DDL, DML, joins, aggregations, stored procedure, window functions basics)
• Programming (Python preferred; Java/Scala acceptable)
• Data concepts (schemas, structured/unstructured data, basic modelling)
• Understanding of software fundamentals: version control (Git), debugging, testing basics.
• Exposure to Azure cloud platform, especially:
• Data storage (Data Lake, blob/object storage)
• Compute (Spark/Databricks/Synapse)
• Event hub/Azure Stream Analytics
• Familiarity with orchestration tools (Synapse and ADF pipeline)
• Understanding of data modelling (star schema, slowly changing dimensions).
• Knowledge of DevOps basics: CI/CD pipelines, IaC (Terraform).
• Any internship/project experience building pipelines or dashboards.

Soft Skills:

• Excellent problem-solving, communication, and stakeholder management skills.
• Ability to balance technical innovation with business value delivery.
• Business acumen: A level-headed, clear communicator to gain detailed level of understanding of organizational business requirements and business dynamics.
• Self-Motivated and able to work independently.
• Attention to detail
• Collaborative
• Team Player
• Decisive
• Supportive
• Passionate
• Professional
• Accountable