Data Engineer - Cloud Data Platforms - Hyderabad

Role & responsibilities

• Design, develop, and maintain

  scalable ETL/ELT pipelines

  for data ingestion, transformation, and load.
• Build automated ingestion frameworks from

  multiple source systems

  ERP, CRM, APIs, IoT, databases, and third-party platforms.
• Work extensively on

  cloud-native data engineering solutions

  , preferably Microsoft Azure (ADF, Data Lake, Integration Services).
• Collaborate with integration teams to work with

  REST, SOAP, OData

  and middleware tools for source-to-cloud connectivity.
• Develop

  data models

  for analytical and operational use cases, including star/snowflake schemas.
• Optimize data storage using

  partitioning, compression, indexing

  , and modern data lakehouse practices.
• Implement

  data validation, reconciliation, monitoring

  , and ensure accuracy, completeness, and lineage documentation.
• Support data scientists, analysts, and BI developers by delivering curated, reliable datasets for ML models and dashboards.
• Ensure compliance with enterprise standards for

  data security, encryption, access controls, and monitoring

  .
• Troubleshoot pipeline failures and maintain detailed documentation of workflows and transformations.

Preferred candidate profile

• 5-10 years

  of data engineering experience.
• Strong expertise in

  Python

  and

  SQL

  .
• Hands-on experience with

  cloud data platforms

  (Azure preferred; AWS/GCP also relevant).
• Experience with modern

  ETL tools

  Azure Data Factory, Talend, Informatica, Apache NiFi, etc.
• Working exposure to big data ecosystem (Spark, Hadoop, Kafka – preferred).
• Data modelling skills – star, snowflake, and performance-optimized models.
• Experience with

  APIs, middleware, integration services

  , and structured/unstructured data sources.
• Familiarity with data governance tools (Purview/Collibra/Alation), version control, and CI/CD tools (Git, Azure DevOps).

vali@strikeitrite.com