Senior Cloud Data Engineer

Bengaluru - India

Monthly Salary: Not Disclosed

Posted on: Yesterday

Vacancies: 1 Vacancy

Job Summary

Senior Cloud Data Engineer

Req number:

R7366

Employment type:

Full time

Worksite flexibility:

Remote

Who we are

CAI is a global services firm with over 9000 associates worldwide and a yearly revenue of $1.3 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 rightwhatever 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

We are seeking a highly skilled Senior Cloud Data Engineer to join our dynamic team. As a Senior Data Engineer you will play a crucial role in to manage the existing cloud data platform to make it more scalable reliable and cost efficient. You will also work on additional projects that would leverage the existing architecture in some cases and use newer technologies where needed. This position will be full-time and remote.

Job Description

We are seeking a Senior Cloud Data Engineer who will manage the existing cloud data platform to make it more scalable reliable and cost efficient. This position will be Full-time and Remote position.

What Youll 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 Youll Need

Required

812 years of experience in data engineering data warehousing or big data platform development.
5 years of hands-on experience with Databricks including Spark Delta Lake and performance optimization.
4 years of experience designing and implementing cloud-based data lake or lakehouse architectures on Databricks.
Strong expertise in Spark technologies including Spark SQL PySpark or Scala.
Advanced SQL and PL/SQL skills with the ability to interpret and refactor legacy stored procedures.
Strong understanding of data modeling techniques including Star Schema Snowflake and modern Lakehouse modeling approaches.
Proficiency in at least one programming language (Python Scala Java).
Hands-on experience with data modeling and warehouse design principles.
Experience designing enterprise-scale ETL/ELT pipelines and ingestion frameworks.
Strong understanding of performance tuning partitioning strategies and cost optimization for large-scale data platforms.
Experience implementing CI/CD pipelines and DevOps practices for data engineering workflows.
Bachelors 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

We Value

Databricks Professional or Associate Cloud Certification.
Experience with enterprise data governance metadata management and data catalog platforms.

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).

Required Experience:

Senior IC

Senior Cloud Data EngineerReq number:R7366Employment type:Full timeWorksite flexibility:RemoteWho we areCAI is a global services firm with over 9000 associates worldwide and a yearly revenue of $1.3 billion. We have over 40 years of excellence in uniting talent and technology to power the possible f...

Senior Cloud Data Engineer

Req number:

R7366

Employment type:

Full time

Worksite flexibility:

Remote

Who we are

Job Summary

Job Description

What Youll 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 Youll Need

Required

812 years of experience in data engineering data warehousing or big data platform development.
5 years of hands-on experience with Databricks including Spark Delta Lake and performance optimization.
4 years of experience designing and implementing cloud-based data lake or lakehouse architectures on Databricks.
Strong expertise in Spark technologies including Spark SQL PySpark or Scala.
Advanced SQL and PL/SQL skills with the ability to interpret and refactor legacy stored procedures.
Strong understanding of data modeling techniques including Star Schema Snowflake and modern Lakehouse modeling approaches.
Proficiency in at least one programming language (Python Scala Java).
Hands-on experience with data modeling and warehouse design principles.
Experience designing enterprise-scale ETL/ELT pipelines and ingestion frameworks.
Strong understanding of performance tuning partitioning strategies and cost optimization for large-scale data platforms.
Experience implementing CI/CD pipelines and DevOps practices for data engineering workflows.
Bachelors 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