Payment Data Developer

Status
Open
Remote policy
Remote
Employment type
Not stated
Salary
Not stated
Categories
Data-Engineering, ETL-Developer, Data-Developer, Payment-Data-Engineering, Data-Pipeline-Engineer, Payments-Data-Software-Engineer
Tech
awsjenkins
Source
himalayas
First observed
2026-08-22 16:00 UTC
Last seen
2026-08-22 16:00 UTC
Source claims posted
2026-08-22 15:55 UTC
Consecutive misses
0 of 10

What the posting says

Minimum requirements:

Responsibilities:

Accountable for producing a consistent and easily accessible data layer that exposes accurate representations of business rules.

Responsibilities will include - ETL development - Storage management - Data Provisioning Database development and maintenance

Develop high quality data retrieval, storage & distribution design and architecture in a test driven & domain driven / cross domain environment

Design and deploy solutions in conjunction with other business units to improve efficiency and consistency of delivery.

Guide the process to maintain a reflexive and pre-emptive space with strong customer focus

Create & Maintain Sophisticated CI / CD Pipelines (authoring & supporting CI/CD pipelines in Jenkins or similar tools and deploy to multi-site environments supporting and managing your applications all the way to production)

Take accountability for deeply understanding the technical landscape and bank wide architecture that is connected to or dependent on the business area supported in order to effectively design & deliver data solutions (architecture, pipeline etc.)

Leverage state of the art relational and No-SQL databases as well integration and streaming platforms do deliver sustainable business specific data solutions.

Strategically & operationally monitor the performance of data products and services ensuring ongoing optimization & cost to value for our businesses (think bank wide)

Automate tasks through appropriate tools and scripting technologies e.g. AWS tools, SQL tools

Debug existing source code and polish feature sets.

Assemble large, complex data sets that meet business requirements & manage the data pipeline

Build infrastructure to automate extremely high volumes of data delivery and Creatively solve data volume and scaling challenges

Ensure designs & solutions support the technical organisation principles of self-service, repeatability, testability, scalability & resilience

Apply general design patterns and paradigms to deliver technical solutions

Inform & support the infrastructure build required for optimal extraction, transformation, and loading of data from a wide variety of data sources.

Responsible for the smooth running of data ingestion and provisioning thereof, working on conjunction with channel managers to ensure smooth flows of data.

This will include the development of short term solutions and the subsequent migration onto permanent mass storage across multiple technologies.

Continuously optimise, improve & automate data retrieval, storage & distribution processes

Work across the value chain and in particular with QA & CSO to define and implement quality assurance routines & processes

Collaborate with data science teams & broader business & technical stakeholders to analyse customer data requirements & leverage analysis to identify & accurately spec / frame & set the appropriate data architecture for the business area

Leverage expertise in analytical & creative problem solving to synthesise data solution designs (build a solution from its components) beyond the analysis of the problem

Meaningfully contribute & ensure solutions align to the design & direction of the Group Architecture & in particular data standards, principles, preferences & practices.

Short term deployment must align to strategic long term delivery.

Stay ahead of the curve on data retrieval, storage & distribution technologies & processes (global best practices & trends) ensuring best practice.

Ensure solutions align to the design and direction of the Group Infrastructure standards and practices e.g. OLAs, IAAS, PAAS, SAAS, DAAS Containerisation etc.

Adhere to Business data storage requirements as well as an legislation

Provide consulting and learning to other areas to continually create a fertile area for data centric thinking. - Knowledge sharing - Mentoring

Take one stop shop accountability for the retrieval, storage, processing & distribution of data across a business area (data eco-system)

Perform all other duties as reasonably assigned.

Originally posted on Himalayas

Quality

Completeness: 65%

Not enough history yet to judge honesty signals.

Timeline

  1. *
    #273210 2026-08-22 16:00 UTC
    Published