About Oracle FSGIU - Finergy:
Finergy division within Oracle FSGIU exclusively focuses on the Banking, Financial Services, and Insurance (BFSI) sector, offering deep domain knowledge to address complex financial needs. Finergy has Industry expertise in BFSI. ( On Accelerated Implementation
) Finergy has Proven methodologies that fast-track the deployment of multi-channel delivery platforms, minimizing IT intervention and reducing time to market. Due to Personalization tools that tailor customer experiences, Finergy has several loyal customers for over a decade. ( On End-to-End Banking Solutions
) Finergy Provides a single platform for a wide range of banking services trade, treasury, cash management enhancing operational efficiency with integrated dashboards and analytics. Finergy offers Expert Consulting Services
, Comprehensive consulting support, from strategy development to solution implementation, ensuring the alignment of technology with business goals.
Job Responsibilities
- Design, develop, and optimize
data processing pipelines
using PySpark
on AWS Databricks
, ensuring scalability and high performance. - Implement
data ingestion
, transformation
, and aggregation workflows
to support advanced analytics and enterprise reporting needs. - Collaborate with cross-functional teams to build
cloud-native data solutions
leveraging AWS services
such as S3
and EC2
. - Write efficient
Python code
for automation, orchestration, and integration of data workflows across environments. - Ensure data quality, reliability, and governance through the implementation of
best practices
, including error handling, auditing, and logging. - Participate in performance tuning of
PySpark jobs
, cloud cost optimization, and continuous improvement of the data platform.
Mandatory Skills:
- 4 to 8 years of professional and relevant experience in software industry.
- Strong hands-on expertise in
PySpark
for distributed data processing and transformation. - Proven experience with
Python programming
, including implementing reusable, production-grade code. - Practical knowledge of
AWS Databricks
for building and orchestrating large-scale data pipelines. - Demonstrated experience in processing structured and unstructured data using
Spark clusters
and cloud data platforms. - Ability to apply
data engineering best practices
including version control, CI/CD for data pipelines, and performance tuning.
Preferred Skills:
- Working knowledge of
SQL
for data querying, analysis, and troubleshooting. - Experience using
AWS S3
for object storage and EC2
for compute orchestration in cloud environments. - Understanding of
cloud-native data architectures
and principles of data security and governance. - Exposure to BFSI domain use cases and familiarity with handling sensitive financial data.
- Familiarity with CI/CD tools and cloud-native deployment practices.
- Familiarity with
ETL scripting
and data pipeline automation. - Knowledge of
big data ecosystems
and distributed computing.
Career Level - IC2
About Oracle FSGIU - Finergy:
Finergy division within Oracle FSGIU exclusively focuses on the Banking, Financial Services, and Insurance (BFSI) sector, offering deep domain knowledge to address complex financial needs. Finergy has Industry expertise in BFSI. ( On Accelerated Implementation
) Finergy has Proven methodologies that fast-track the deployment of multi-channel delivery platforms, minimizing IT intervention and reducing time to market. Due to Personalization tools that tailor customer experiences, Finergy has several loyal customers for over a decade. ( On End-to-End Banking Solutions
) Finergy Provides a single platform for a wide range of banking services trade, treasury, cash management enhancing operational efficiency with integrated dashboards and analytics. Finergy offers Expert Consulting Services
, Comprehensive consulting support, from strategy development to solution implementation, ensuring the alignment of technology with business goals.
Job Responsibilities
- Design, develop, and optimize
data processing pipelines
using PySpark
on AWS Databricks
, ensuring scalability and high performance. - Implement
data ingestion
, transformation
, and aggregation workflows
to support advanced analytics and enterprise reporting needs. - Collaborate with cross-functional teams to build
cloud-native data solutions
leveraging AWS services
such as S3
and EC2
. - Write efficient
Python code
for automation, orchestration, and integration of data workflows across environments. - Ensure data quality, reliability, and governance through the implementation of
best practices
, including error handling, auditing, and logging. - Participate in performance tuning of
PySpark jobs
, cloud cost optimization, and continuous improvement of the data platform.
Mandatory Skills:
- 4 to 8 years of professional and relevant experience in software industry.
- Strong hands-on expertise in
PySpark
for distributed data processing and transformation. - Proven experience with
Python programming
, including implementing reusable, production-grade code. - Practical knowledge of
AWS Databricks
for building and orchestrating large-scale data pipelines. - Demonstrated experience in processing structured and unstructured data using
Spark clusters
and cloud data platforms. - Ability to apply
data engineering best practices
including version control, CI/CD for data pipelines, and performance tuning.
Preferred Skills:
- Working knowledge of
SQL
for data querying, analysis, and troubleshooting. - Experience using
AWS S3
for object storage and EC2
for compute orchestration in cloud environments. - Understanding of
cloud-native data architectures
and principles of data security and governance. - Exposure to BFSI domain use cases and familiarity with handling sensitive financial data.
- Familiarity with CI/CD tools and cloud-native deployment practices.
- Familiarity with
ETL scripting
and data pipeline automation. - Knowledge of
big data ecosystems
and distributed computing.
