Cloud Data Engineer

CloudAI Technologies; Hyderabad; Hybrid; INR 1,800,000 - 2,400,000; Full time

Job summary

CloudAI Technologies in Hyderabad is seeking a seasoned Cloud Data Engineer to design, build, and maintain modern cloud data platforms and pipelines. You will work with Databricks, Snowflake, AWS and/or Azure to support analytics, reporting, AI/ML, and enterprise applications.

The role emphasizes designing scalable data pipelines, data lakes/lakehouses, and data warehouses, with hands-on experience in SQL, Python and Spark/PySpark to transform and optimize data flows.

Qualifications

• 5+ years of professional data engineering experience.
• Hands-on experience with Databricks and/or Snowflake.
• Experience with AWS and/or Azure data services.
• Experience designing or building data lakes or lakehouse architectures.
• Strong SQL skills.
• Proficiency with Python and PySpark/Spark.
• Experience building production-grade ETL/ELT pipelines.
• Understanding of dimensional modeling, data warehousing, and modern data architecture.
• Experience with cloud object storage such as Amazon S3 or Azure Data Lake Storage.

Responsibilities

• Design, develop, and maintain scalable data pipelines and cloud data platforms.
• Build and support data lakes, lakehouses, and cloud data warehouses.
• Develop solutions using Databricks and/or Snowflake.
• Implement data solutions on AWS and Azure.
• Develop batch and streaming data pipelines.
• Ingest and transform structured, semi-structured, and unstructured data from various sources.
• Implement data transformation and processing using SQL, Python and Spark/PySpark.
• Design efficient data models and curated data layers for analytics and downstream applications.
• Implement data quality, validation, monitoring, logging, and error-handling frameworks.
• Collaborate with architects, analysts, AI engineers, developers, and client stakeholders.

Skills

Databricks

Snowflake

SQL

Python

PySpark

Data modeling

CI/CD

Git

Tools

Databricks

Snowflake

AWS

Azure

Python

PySpark

SQL

Git

CI/CD

S3

ADLS

Job description

CloudAI Technologies is looking for a Cloud Data Engineer to design, build, and maintain modern cloud data platforms and pipelines. The ideal candidate has hands-on experience with Databricks, Snowflake, AWS and/or Azure and has worked on enterprise data lakes, lakehouses, data warehouses, and large‑scale data integration solutions.

You will work with our cloud, data, AI, and application engineering teams to build scalable data platforms that support analytics, reporting, AI/ML, and enterprise applications.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and cloud data platforms.
• Build and support data lakes, lakehouses, and cloud data warehouses.
• Develop solutions using Databricks and/or Snowflake.
• Implement data solutions on AWS and Azure.
• Develop batch and, where required, streaming data pipelines.
• Ingest and transform structured, semi-structured, and unstructured data from databases, APIs, SaaS platforms, files, and cloud storage.
• Implement data transformation and processing using SQL, Python and Spark/PySpark.
• Design efficient data models and curated data layers for analytics and downstream applications.
• Implement data quality, validation, monitoring, logging, and error‑handling frameworks.
• Optimize pipelines and workloads for performance, reliability, and cloud cost.
• Work with DevOps/platform teams to implement CI/CD and Infrastructure‑as‑Code practices for data workloads.
• Support data governance, metadata, lineage, security, and access‑control requirements.
• Troubleshoot production data issues and participate in root‑cause analysis.
• Collaborate with architects, analysts, AI engineers, developers, and client stakeholders.

Required Qualifications

• 5+ years of professional data engineering experience.
• Strong hands‑on experience with Databricks and/or Snowflake.
• Experience with AWS and/or Azure data services.
• Practical experience designing or building data lakes or lakehouse architectures.
• Strong SQL skills.
• Proficiency with Python and PySpark/Spark.
• Experience building production‑grade ETL/ELT pipelines.
• Understanding of dimensional modeling, data warehousing, and modern data architecture.
• Experience with cloud object storage such as Amazon S3 or Azure Data Lake Storage.
• Familiarity with Git and CI/CD practices.
• Strong troubleshooting and analytical skills.

Preferred Qualifications

Experience with Delta Lake, Unity Catalog, Snowflake Snowpark, AWS Glue, Azure Data Factory, Microsoft Fabric, Kafka/Event Hubs/Kinesis, dbt, Terraform, data governance/catalog platforms, or enterprise AI/ML data pipelines is advantageous.