21,558 Cloud Data Engineer jobs in India

Key Responsibilities:

• Design, develop, and maintain cloud-based solutions on Azure or AWS.

• Implement and manage real-time data streaming and messaging systems using Kafka.

• Develop scalable applications and services using Java and Python.

• Deploy, manage, and monitor containerized applications using Kubernetes.

• Build and optimize big data processing pipelines using Databricks.

• Manage and maintain databases, including SQL Server and Snowflake, and write

complex SQL scripts.

• Work with Unix/Linux commands to manage and monitor system operations.

• Collaborate with cross-functional teams to ensure seamless integration of cloud-based

solutions.

Key Skills:

• Expertise in Azure or AWS cloud platforms.

• Proficiency in Kafka, Java, Python, and Kubernetes.

• Hands-on experience with Databricks for big data processing.

• Strong database management skills with SQL Server, Snowflake, and advanced SQL

scripting.

• Solid understanding of Unix/Linux commands.

General Requirements for Both Off-Shore Roles:

• Bachelor’s degree in computer science, Engineering, or a related field (or equivalent

experience).

• 5+ years of experience in cloud and data engineering roles.

• Strong problem-solving and analytical skills.

• Excellent communication and collaboration abilities.

• Proven ability to work in a fast-paced, agile environment.

Key Responsibilities:

• Design, develop, and maintain cloud-based solutions on Azure or AWS.

• Implement and manage real-time data streaming and messaging systems using Kafka.

• Develop scalable applications and services using Java and Python.

• Deploy, manage, and monitor containerized applications using Kubernetes.

• Build and optimize big data processing pipelines using Databricks.

• Manage and maintain databases, including SQL Server and Snowflake, and write

complex SQL scripts.

• Work with Unix/Linux commands to manage and monitor system operations.

• Collaborate with cross-functional teams to ensure seamless integration of cloud-based

solutions.

Key Skills:

• Expertise in Azure or AWS cloud platforms.

• Proficiency in Kafka, Java, Python, and Kubernetes.

• Hands-on experience with Databricks for big data processing.

• Strong database management skills with SQL Server, Snowflake, and advanced SQL

scripting.

• Solid understanding of Unix/Linux commands.

General Requirements for Both Off-Shore Roles:

• Bachelor’s degree in computer science, Engineering, or a related field (or equivalent

experience).

• 5+ years of experience in cloud and data engineering roles.

• Strong problem-solving and analytical skills.

• Excellent communication and collaboration abilities.

• Proven ability to work in a fast-paced, agile environment.

Key Responsibilities:

• Design, develop, and maintain cloud-based solutions on Azure or AWS.

• Implement and manage real-time data streaming and messaging systems using Kafka.

• Develop scalable applications and services using Java and Python.

• Deploy, manage, and monitor containerized applications using Kubernetes.

• Build and optimize big data processing pipelines using Databricks.

• Manage and maintain databases, including SQL Server and Snowflake, and write

complex SQL scripts.

• Work with Unix/Linux commands to manage and monitor system operations.

• Collaborate with cross-functional teams to ensure seamless integration of cloud-based

solutions.

Key Skills:

• Expertise in Azure or AWS cloud platforms.

• Proficiency in Kafka, Java, Python, and Kubernetes.

• Hands-on experience with Databricks for big data processing.

• Strong database management skills with SQL Server, Snowflake, and advanced SQL

scripting.

• Solid understanding of Unix/Linux commands.

General Requirements for Both Off-Shore Roles:

• Bachelor’s degree in computer science, Engineering, or a related field (or equivalent

experience).

• 5+ years of experience in cloud and data engineering roles.

• Strong problem-solving and analytical skills.

• Excellent communication and collaboration abilities.

• Proven ability to work in a fast-paced, agile environment.

Req number:

Employment type:

Worksite flexibility:

CAI is a global technology services firm with over 8,500 associates worldwide and a yearly revenue of $1 billion+. We have over 40 years of excellence in uniting talent and technology to power the possible for our clients, colleagues, and communities. As a privately held company, we have the freedom and focus to do what is right—whatever it takes. Our tailor-made solutions create lasting results across the public and commercial sectors, and we are trailblazers in bringing neurodiversity to the enterprise.

Job Summary

Job Description

What You’ll Do

• Analyze and understand existing data warehouse implementations to support migration and consolidation efforts.
• Reverse-engineer legacy stored procedures (PL/SQL, SQL) and translate business logic into scalable Spark SQL code within Databricks notebooks.
• Design and develop data lake solutions on AWS using S3 and Delta Lake architecture, leveraging Databricks for processing and transformation.
• Build and maintain robust data pipelines using ETL tools with ingestion into S3 and processing in Databricks.
• Collaborate with data architects to implement ingestion and transformation frameworks aligned with enterprise standards.
• Evaluate and optimize data models (Star, Snowflake, Flattened) for performance and scalability in the new platform.
• Document ETL processes, data flows, and transformation logic to ensure transparency and maintainability.
• Perform foundational data administration tasks including job scheduling, error troubleshooting, performance tuning, and backup coordination.
• Work closely with cross-functional teams to ensure smooth transition and integration of data sources into the unified platform.
• Participate in Agile ceremonies and contribute to sprint planning, retrospectives, and backlog grooming.
• Triage, debug and fix technical issues related to Data Lakes.
• Maintain and Manage Code repositories like Git.

What You'll Need

• 5+ years of experience working with Databricks , including Spark SQL and Delta Lake implementations.
• 3 + years of experience in designing and implementing data lake architectures on Databricks.
• Strong SQL and PL/SQL skills with the ability to interpret and refactor legacy stored procedures.
• Hands-on experience with data modeling and warehouse design principles.
• Proficiency in at least one programming language (Python, Scala, Java).
• Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or related field.
• Experience working in Agile environments and contributing to iterative development cycles. Experience working on Agile projects and Agile methodology in general.
• Databricks cloud certification is a big plus.
• Exposure to enterprise data governance and metadata management practices.

Physical Demands

• This role involves mostly sedentary work, with occasional movement around the office to attend meetings, etc.
• Ability to perform repetitive tasks on a computer, using a mouse, keyboard, and monitor.

Reasonable accommodation statement

If you require a reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employment selection process, please direct your inquiries to or (888) 824 – 8111.

Key Responsibilities:

Design and Development :

• Design, develop, and maintain scalable ETL pipelines using cloud-native tools (AWS DMS, AWS Glue, Kafka, Azure Data Factory, GCP Dataflow, etc.).
• Architect and implement data lakes and data warehouses on cloud platforms (AWS, Azure, GCP).
• Develop and optimize data ingestion, transformation, and loading processes using Databricks, Snowflake, Redshift, BigQuery and Azure Synapse.
• Implement ETL processes using tools like Informatica, SAP Data Intelligence, and others.
• Develop and optimize data processing jobs using Spark Scala.

Data Integration and Management :

• Integrate various data sources, including relational databases, APIs, unstructured data, and ERP systems into the data lake.
• Ensure data quality and integrity through rigorous testing and validation.
• Perform data extraction from SAP or ERP systems when necessary.

Performance Optimization:

• Monitor and optimize the performance of data pipelines and ETL processes.
• Implement best practices for data management, including data governance, security, and compliance.

Collaboration and Communication :

• Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions.
• Collaborate with cross-functional teams to design and implement data solutions that meet business needs.

Documentation and Maintenance:

• Document technical solutions, processes, and workflows.
• Maintain and troubleshoot existing ETL pipelines and data integrations.

Education:

• Bachelor s degree in Computer Science, Information Technology, or a related field. Advanced degrees are a plus.

Experience:

• 7+ years of experience as a Data Engineer or in a similar role.
• Proven experience with cloud platforms: AWS, Azure, and GCP.
• Hands-on experience with cloud-native ETL tools such as AWS DMS, AWS Glue, Kafka, Azure Data Factory, GCP Dataflow, etc.
• Experience with other ETL tools like Informatica, SAP Data Intelligence, etc.
• Experience in building and managing data lakes and data warehouses.
• Proficiency with data platforms like Redshift, Snowflake, BigQuery, Databricks, and Azure Synapse.
• Experience with data extraction from SAP or ERP systems is a plus.
• Strong experience with Spark and Scala for data processing.

Skills:

• Strong programming skills in Python, Java, or Scala.
• Proficient in SQL and query optimization techniques.
• Familiarity with data modeling, ETL/ELT processes, and data warehousing concepts.
• Knowledge of data governance, security, and compliance best practices.
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration skills.

Preferred Qualifications:

• Experience with other data tools and technologies such as Apache Spark, or Hadoop.
• Certifications in cloud platforms (AWS Certified Data Analytics - Specialty, Google Professional Data Engineer, Microsoft Certified: Azure Data Engineer Associate).
• Experience with CI/CD pipelines and DevOps practices for data engineering
• Selected applicant will be subject to a background investigation, which will be conducted and the results of which will be used in compliance with applicable law.

• Design and develop scalable ETL/ELT pipelines using Dataflow, Dataproc, Apache Beam, Cloud Composer (Airflow) , and other GCP services.
• Build and maintain data lakes and data warehouses using BigQuery , Cloud Storage , and Cloud SQL/Spanner .
• Implement and optimize data ingestion from a variety of structured and unstructured sources using GCP-native tools and APIs.
• Work with Pub/Sub , Cloud Functions , and Eventarc for real-time data processing and streaming pipelines.
• Ensure data governance , quality , and security using best practices for IAM, encryption, data cataloging, and auditing.
• Collaborate with stakeholders to gather requirements, define data models, and deliver insights via BI tools.
• Automate workflows and monitoring using tools like Cloud Monitoring , Logging , and Terraform or Deployment Manager .
• Stay current with the latest GCP tools, features, and trends in cloud data engineering.

• Bachelor's degree in Computer Science, Data Engineering, or related field.
• 3+ years of experience in data engineering, including at least 1–2 years on Google Cloud Platform .
• Proficiency with SQL , Python , and/or Java for data processing and scripting.
• Hands-on experience with GCP services like:
• BigQuery
• Cloud Storage
• Dataflow / Dataproc
• Pub/Sub
• Composer
• Cloud Functions
• Solid understanding of data modeling, partitioning, performance tuning, and schema design.
• Experience with DevOps practices and CI/CD pipelines for data projects.

Job Title : Cloud Data Engineer

Experience : 4 to 5 Years

Location : Noida / Gurgaon / Hyderabad / Bangalore / Pune

Notice Period : Immediate (15 Days notice period)

• Design, develop, and maintain automated data pipelines and ETL processes .
• Create and optimize data tables and views in Snowflake .
• Work with datasets across Azure , AWS , and various structured/unstructured formats.
• Ensure data security, privacy, and compliance with industry and organizational standards (e.g., BHP standards).
• Support and mentor junior team members by providing guidance on data modelling, data management, and data engineering best practices .

• Strong hands-on experience in data pipeline development , ETL scripting using Python , and handling data formats like JSON, CSV , etc.
• Proficiency in AWS services such as:
• AWS Glue
• AWS Batch
• AWS Step Functions
• Experience with Azure services , including:
• Azure Data Factory
• Azure Logic Apps
• Azure Functions
• Azure Blob Storage
• Solid understanding of:
• Data management principles
• Data structures & storage solutions
• Data modeling techniques
• Strong programming skills in:
• Python (with OOP concepts)
• PowerShell
• Bash scripting
• Advanced SQL skills, including writing and optimizing complex queries .
• Working experience with Terraform and CI/CD pipelines for infrastructure and deployment automation.

Job Title : Cloud Data Engineer

Experience : 4 to 5 Years

Location : Noida / Gurgaon / Hyderabad / Bangalore / Pune

Notice Period : Immediate (15 Days notice period)

• Design, develop, and maintain automated data pipelines and ETL processes .
• Create and optimize data tables and views in Snowflake .
• Work with datasets across Azure , AWS , and various structured/unstructured formats.
• Ensure data security, privacy, and compliance with industry and organizational standards (e.g., BHP standards).
• Support and mentor junior team members by providing guidance on data modelling, data management, and data engineering best practices .

• Strong hands-on experience in data pipeline development , ETL scripting using Python , and handling data formats like JSON, CSV , etc.
• Proficiency in AWS services such as:
• AWS Glue
• AWS Batch
• AWS Step Functions
• Experience with Azure services , including:
• Azure Data Factory
• Azure Logic Apps
• Azure Functions
• Azure Blob Storage
• Solid understanding of:
• Data management principles
• Data structures & storage solutions
• Data modeling techniques
• Strong programming skills in:
• Python (with OOP concepts)
• PowerShell
• Bash scripting
• Advanced SQL skills, including writing and optimizing complex queries .
• Working experience with Terraform and CI/CD pipelines for infrastructure and deployment automation.