Cloud Data Engineer
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Summary
Designs, builds, and maintains scalable cloud data platforms and ETL/ELT pipelines using AWS, Databricks, and Informatica IDMC. Day to day involves data integration and quality work, Spark/Databricks processing, performance tuning, and automating workflows with services like Lambda, Step Functions, and Glue.
Job Role:-
Cloud Data Engineer
Job Location:-
Singapore
Experience
:- 4-5 Years
Position Summary:- We are seeking a
Cloud Data Engineer
to design, develop, and maintain scalable data platforms and pipelines using
AWS, Databricks, and Informatica IDMC
. The role will focus on data integration, ETL/ELT, data quality, governance, security, performance, and automation.
Roles & Responsibilities:-
Design, develop, and maintain scalable
data pipelines and cloud data platforms
using AWS, Databricks, and Informatica IDMC. Manage data storage and processing using
Amazon S3, RDS, Redshift, DynamoDB, Delta Lake
, and related services. Develop and optimize
ETL/ELT pipelines
for data ingestion, transformation, cleansing, and enrichment. Integrate data from multiple internal and external sources while ensuring
data quality, consistency, and reliability
. Develop data processing solutions using
Databricks and Apache Spark
. Use
Informatica IDMC
for data integration, data quality, metadata, and governance. Monitor and optimize
data pipeline, query, and processing performance
for scalability and reliability. Implement
data security, access controls, encryption, and governance
in cloud data environments. Automate data workflows using
AWS Lambda, Step Functions, Databricks Jobs
, and Informatica IDMC. Troubleshoot data pipeline and platform issues and implement corrective and preventive measures. Maintain technical documentation, data workflows, and operational procedures. Collaborate with data, technology, and business stakeholders to understand requirements and deliver data solutions.
Required Skills:- AWS:
S3, RDS, Redshift, DynamoDB, Lambda, Glue, Step Functions. Databricks:
Delta Lake, Spark, Databricks Jobs, data processing. Informatica:
IDMC, data integration, data quality, metadata/governance. Strong knowledge of
ETL/ELT, data pipelines, data lakes, and data warehouses
. Strong
SQL
and data transformation skills. Experience with
Python and/or PySpark
. Knowledge of
cloud data security, governance, and data quality
. Experience with
monitoring, troubleshooting, and performance optimization
. Understanding of
CI/CD and automation
for data engineering workflows.
Requirements / Qualifications:-
45+ years of experience
in data engineering, cloud data platforms, or related IT roles. Bachelors degree in
Computer Science, Information Technology, Engineering, Data Science, or a related field
, or equivalent practical experience. Hands-on experience developing and maintaining
cloud-based data pipelines
. Practical experience with
AWS and Databricks
. Experience with
Informatica IDMC
or comparable enterprise data integration platforms. Strong analytical and problem-solving skills. Good communication and collaboration skills. Ability to work effectively with cross-functional teams in a diverse work environment.
Preferred:-
Experience with
data governance, metadata management, and data quality frameworks
. Experience with
AWS certifications, Databricks certifications, or Informatica certifications
. Experience in
large-scale or enterprise data environments
.
Cloud Data Engineer
Job Location:-
Singapore
Experience
:- 4-5 Years
Position Summary:- We are seeking a
Cloud Data Engineer
to design, develop, and maintain scalable data platforms and pipelines using
AWS, Databricks, and Informatica IDMC
. The role will focus on data integration, ETL/ELT, data quality, governance, security, performance, and automation.
Roles & Responsibilities:-
Design, develop, and maintain scalable
data pipelines and cloud data platforms
using AWS, Databricks, and Informatica IDMC. Manage data storage and processing using
Amazon S3, RDS, Redshift, DynamoDB, Delta Lake
, and related services. Develop and optimize
ETL/ELT pipelines
for data ingestion, transformation, cleansing, and enrichment. Integrate data from multiple internal and external sources while ensuring
data quality, consistency, and reliability
. Develop data processing solutions using
Databricks and Apache Spark
. Use
Informatica IDMC
for data integration, data quality, metadata, and governance. Monitor and optimize
data pipeline, query, and processing performance
for scalability and reliability. Implement
data security, access controls, encryption, and governance
in cloud data environments. Automate data workflows using
AWS Lambda, Step Functions, Databricks Jobs
, and Informatica IDMC. Troubleshoot data pipeline and platform issues and implement corrective and preventive measures. Maintain technical documentation, data workflows, and operational procedures. Collaborate with data, technology, and business stakeholders to understand requirements and deliver data solutions.
Required Skills:- AWS:
S3, RDS, Redshift, DynamoDB, Lambda, Glue, Step Functions. Databricks:
Delta Lake, Spark, Databricks Jobs, data processing. Informatica:
IDMC, data integration, data quality, metadata/governance. Strong knowledge of
ETL/ELT, data pipelines, data lakes, and data warehouses
. Strong
SQL
and data transformation skills. Experience with
Python and/or PySpark
. Knowledge of
cloud data security, governance, and data quality
. Experience with
monitoring, troubleshooting, and performance optimization
. Understanding of
CI/CD and automation
for data engineering workflows.
Requirements / Qualifications:-
45+ years of experience
in data engineering, cloud data platforms, or related IT roles. Bachelors degree in
Computer Science, Information Technology, Engineering, Data Science, or a related field
, or equivalent practical experience. Hands-on experience developing and maintaining
cloud-based data pipelines
. Practical experience with
AWS and Databricks
. Experience with
Informatica IDMC
or comparable enterprise data integration platforms. Strong analytical and problem-solving skills. Good communication and collaboration skills. Ability to work effectively with cross-functional teams in a diverse work environment.
Preferred:-
Experience with
data governance, metadata management, and data quality frameworks
. Experience with
AWS certifications, Databricks certifications, or Informatica certifications
. Experience in
large-scale or enterprise data environments
.