Job Description

: Test Data Architect

This job posting is for a senior-level manager who specializes in automating the movement and transformation of data (ETL) within a banking environment.


We are seeking a highly skilled and self-driven

Data Testing Architect

to oversee and own design, build, and deploy of scalable ETL pipelines across hybrid environments including Cloudera Hadoop, Red Hat OpenShift, and AWS Cloud. This role focuses on developing robust PySpark-based data processing solutions, building testing frameworks for ETL jobs, and leveraging containerization and orchestration platforms like Docker and AWS EKS for scalable workloads.


You will be responsible for automating ETL processes, integrating with data lakes and data warehouses, managing large datasets efficiently, and ensuring reliable data delivery through CI/CD-enabled workflows.

What You'll Do (Developer Focus):

Build Data Pipelines:

Create testing solutions to extract data from various sources (like databases and data lakes), clean and transform it, and load it into target systems

Testing and Validation:

Develop automated tests to ensure the data pipelines are working correctly and the data is accurate. This is like quality control, making sure everything meets the bank's standards

Containerization and Orchestration:

Package these data pipelines into containers (using Docker) and manage their execution using orchestration tools (like AWS EKS)

Cloud Integration:

Work with various cloud services (like AWS S3, Lambda, and Airflow) for data storage, processing, and scheduling

Test Data Management

- Oversee test data strategies and environment simulations for scalable, reliable automation. Experience with synthetic data generation Build and maintain

ETL validation and testing scripts

that run on

Red Hat OpenShift

containers Work with

Hive, HDFS, and Oracle

data sources to extract, transform, and load large-scale datasets Develop

Dockerfiles

and create container images for PySpark jobs Deploy and orchestrate ETL jobs using

AWS EKS (Elastic Kubernetes Service)

and integrate them into workflows Leverage

AWS services

such as

S3, Lambda, and Airflow

for data ingestion, event-driven processing, and orchestration Design and develop PySpark-based ETL pipelines on

Cloudera Hadoop platform

Create reusable frameworks, libraries, and templates to accelerate automation and testing of ETL jobs Participate in code reviews,

CI/CD pipelines

, and maintain best practices in Spark and cloud-native development Ensures tooling can be run in CICD providing real-time on demand test execution shortening the feedback loop to fully support Handsfree execution Regression, Integration, Sanity testing - provide solutions and ensures timely completion

What You'll Do (Lead Focus):

Team Management:

Lead a team of automation professionals, guiding them on projects and helping them develop their skills Own and maintain automation best practices and educates team via meetings, Demos and Q&A sessions Ensures new utilities are documented and transitioned to testers for execution and supports for troubleshooting in case required

Strategy and Planning:

Define the overall strategy for automating data processes and testing, ensuring it aligns with the bank's goals Lead initiatives related to automation on Data & Analytics testing requirements for process and product rollout into production

Tooling and Innovation:

Research and implement new automation tools and techniques, including AI and machine learning, low-code solutions to improve efficiency Design and develop integrated portal to consolidate utilities and cater to user needs

Collaboration:

Work closely with other teams and partners to ensure smooth data operations and meet regulatory requirements. Cross team collaboration to ensure automated solutions are provided and can be run self sufficient Works with Business/Stakeholders to insure proper test coverage and Incident analysis and prevention

Reporting and Metrics:

Track key performance indicators (KPIs) related to automation for entire D&A team and report on progress to leadership. Automation ROI Analysis: Measure the impact of automation productivity, quality and cost; adjust strategy based on data Provides SMT forward looking agenda, plans, improvements, measured progress Monitors and reviews code check-ins from the Team and helps maintain project repository

Skillset:

12-15 years of experience on data platform testing across data lineage especially with knowledge of regulatory compliance and risk management Detailed knowledge data flows in relational database and Bigdata (Familiarity with Hadoop (a platform for processing massive datasets)). Selenium BDD Cucumber using Java, Python Strong experience with Python broader understanding for batch and stream processing deploying PySpark workloads to AWS EKS (Kubernetes) Proficiency in testing on Cloudera Hadoop ecosystem (HDFS, Hive) and AWS Hands-on experience with ETL Strong knowledge of Oracle SQL and HiveQL Solid understanding of AWS services like S3, Lambda, EKS, Airflow, and IAM Understanding of architecture on cloud with S3, Lamda, Airflow DAGs to orchestrate ETL jobs Familiarity with CI/CD tools (e.g., Jenkins, GitLab CI) Scripting knowledge in Python Version Control: GIT, Bitbucket, GitHub Experience on BI reports validations e.g., Tableau dashboards and views validation Strong understanding of Wealth domain, data regulatory & governance for APAC, EMEA and NAM Strong problem-solving and debugging skills Excellent communication and collaboration abilities to lead and mentor a large techno-functional team across different geographical locations Manage global teams and ability to support multiple time zones

Strong financial Acumen and great presentation skills

Able to work in an Agile environment and deliver results independently

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Job Family Group:

Technology
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Job Family:

Technology Quality
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Time Type:

Full time
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Most Relevant Skills

Please see the requirements listed above.
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Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.
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