Jobs at Djinni

Project Description:

This is a strategic data engineering engagement with our client to architect and plan the migration of their entire data processing and ETL estate from Matillion to AWS Glue — a foundational shift in how one of the world's largest financial market infrastructure companies handles its data pipelines.
During this Mobilisation Phase, you'll work jointly with client's engineering teams to reverse-engineer the existing landscape, design the target-state architecture across every layer (infrastructure, data processing, workflows, dependencies, and operating model), and build the detailed delivery blueprint that will greenlight the full-scale migration.
The work is technically rich and highly collaborative: you'll review and validate job inventories spanning hundreds of ETL workflows, define reusable migration patterns and templates, design a validation and reconciliation framework, run a proof-of-concept to stress-test the approach, and navigate client's rigorous internal governance — from Architectural Significance Assessments through Architectural Review Boards to a formal Gate 1 decision.
This is the kind of engagement where your recommendations directly shape a multi-phase, multi-million-pound programme: the target-state framework you produce here becomes the blueprint that a larger delivery team will execute against. Perfect opportunity for combining deep data engineering knowledge with architecture leadership, stakeholder influence, and structured delivery planning inside a Tier 1 financial services environment

Responsibilities:

-Wave planning — plan migration waves based on system dependencies and priorities
-Complexity assessment — evaluate complexity of each workload/job prior to migration
-Workload analysis — analyze existing batch processes, their dependencies, schedules, and SLAs
-Orchestration migration strategy — design the strategy for migrating from Control-M to AWS Step Functions (job mapping, dependencies, triggers)
-Cutover runbook — develop detailed cutover runbooks (steps, rollback points, success criteria)
-Pod coordination — coordinate across multiple teams/pods involved in the migration
-Release governance — manage release processes, ensuring quality and compliance with standards prior to deployment

Mandatory Skills Description:

- Large-scale migration experience — proven track record on enterprise-scale migration projects
- Wave planning — hands-on experience planning waves in multi-system migrations
- Control-M — deep knowledge of Control-M (jobs, schedules, dependencies, calendars)
- AWS Step Functions — hands-on experience designing and building workflows in Step Functions
- Risk assessment — experience identifying and mitigating risks in migration projects
- Data reconciliation — experience validating data/results post-migration (before/after comparison)
- Release management — experience managing releases in an enterprise environment

Nice-to-Have Skills Description:

- Experience with other orchestration tools (Airflow, AWS Glue Workflows)
- AWS certification (Solutions Architect / DevOps Engineer)
- Knowledge of AWS Lambda, EventBridge (commonly used- alongside Step Functions)
- Experience in financial domain

Project Description:

This is a strategic data engineering engagement with our client to architect and plan the migration of their entire data processing and ETL estate from Matillion to AWS Glue — a foundational shift in how one of the world's largest financial market infrastructure companies handles its data pipelines.
During this Mobilisation Phase, you'll work jointly with client's engineering teams to reverse-engineer the existing landscape, design the target-state architecture across every layer (infrastructure, data processing, workflows, dependencies, and operating model), and build the detailed delivery blueprint that will greenlight the full-scale migration.
The work is technically rich and highly collaborative: you'll review and validate job inventories spanning hundreds of ETL workflows, define reusable migration patterns and templates, design a validation and reconciliation framework, run a proof-of-concept to stress-test the approach, and navigate client's rigorous internal governance — from Architectural Significance Assessments through Architectural Review Boards to a formal Gate 1 decision.
This is the kind of engagement where your recommendations directly shape a multi-phase, multi-million-pound programme: the target-state framework you produce here becomes the blueprint that a larger delivery team will execute against. Perfect opportunity for combining deep data engineering knowledge with architecture leadership, stakeholder influence, and structured delivery planning inside a Tier 1 financial services environment

Responsibilities:

- Design, build, and maintain ETL/ELT pipelines on AWS
- Migrate existing data pipelines and workloads from legacy/on-prem systems to AWS
- Develop and optimize data models for data warehouse/data lake (Redshift, S3)
- Build and orchestrate data workflows (Glue, Step Functions, Lambda, EMR)
- Implement data quality checks, validation, and reconciliation processes
- Optimize pipeline performance and manage compute/storage costs
- Ensure data security and access control (IAM, KMS, encryption)
- Monitor and troubleshoot pipeline failures (CloudWatch, logging)
- Collaborate with data analysts, BI developers, and architects on data requirements
- Document data pipelines, architecture, and operational runbooks

Mandatory Skills Description:

- 5+ years of experience
- Hands-on experience building data pipelines on AWS (Glue, EMR, Lambda, Step Functions)
- Strong SQL and experience with data warehousing (Redshift, dimensional modeling)
- Proficiency in Python or Scala for data engineering
- Experience with S3-based data lake architecture (partitioning, cataloging, formats like Parquet)
- Experience migrating data pipelines from on-prem or other cloud platforms
- Understanding of data governance, security, and access control on AWS
- Experience with CI/CD for data pipelines

Nice-to-Have Skills Description:

- AWS certification (Data Analytics Specialty or Data Engineer Associate)
- Experience with streaming data (Kinesis, MSK/Kafka)
- Familiarity with Infrastructure as Code (Terraform/CloudFormation)
- Experience with orchestration tools (Airflow, dbt)
- Experience in financial domain

• This is a strategic data engineering engagement with our client to architect and plan the migration of their entire data processing and ETL estate from Matillion to AWS Glue — a foundational shift in how one of the world's largest financial market infrastructure companies handles its data pipelines.
  During this Mobilisation Phase, you'll work jointly with client's engineering teams to reverse-engineer the existing landscape, design the target-state architecture across every layer (infrastructure, data processing, workflows, dependencies, and operating model), and build the detailed delivery blueprint that will greenlight the full-scale migration.
  The work is technically rich and highly collaborative: you'll review and validate job inventories spanning hundreds of ETL workflows, define reusable migration patterns and templates, design a validation and reconciliation framework, run a proof-of-concept to stress-test the approach, and navigate client's rigorous internal governance — from Architectural Significance Assessments through Architectural Review Boards to a formal Gate 1 decision.
  This is the kind of engagement where your recommendations directly shape a multi-phase, multi-million-pound programme: the target-state framework you produce here becomes the blueprint that a larger delivery team will execute against. Perfect opportunity for combining deep data engineering knowledge with architecture leadership, stakeholder influence, and structured delivery planning inside a Tier 1 financial services environment

   

• Responsibilities:

  - Agentic AI Migration Framework development — design and build an agentic AI framework to automate and accelerate migration workflowsж
  - Pattern library build — develop and maintain a library of reusable migration patterns/templates for common conversion scenarios;
  -Automated conversion pipeline — build pipelines that automatically convert/transform code and configurations (e.g., Matillion jobs) as part of the migration process;
  -GitHub Copilot integration for code generation — integrate GitHub Copilot into the migration workflow to accelerate code generation and conversion tasks;
  -Support factory pods — provide technical support, tooling, and troubleshooting to migration factory pods executing migrations at scale

   

• Mandatory Skills Description:

  - 2 month project with posibility of extentention

  - Python — strong hands-on Python development experience for building tools and automation
  - GenAI/LLM integration — experience integrating GenAI/LLM capabilities into applications, workflows, or tooling
  - Prompt engineering — hands-on experience designing, testing, and optimizing prompts for LLM-based tools
  - AWS Bedrock — hands-on experience with AWS Bedrock for building GenAI-powered applications
  - GitHub Copilot — practical experience using and/or integrating GitHub Copilot into development workflows
  - Automation frameworks — experience designing and building automation frameworks/tooling from scratch
  - Testing — strong experience with test automation and validation frameworks to ensure conversion accuracy
  - Matillion JSON parsing — experience parsing, interpreting, and transforming Matillion job definitions (JSON format)

   

• Nice-to-Have Skills Description:

  Experience in financial domain

   

• Languages:
  • English: C2 Proficient

Project Description:

This is a strategic data engineering engagement with our client to architect and plan the migration of their entire data processing and ETL estate from Matillion to AWS Glue — a foundational shift in how one of the world's largest financial market infrastructure companies handles its data pipelines.
During this Mobilisation Phase, you'll work jointly with client's engineering teams to reverse-engineer the existing landscape, design the target-state architecture across every layer (infrastructure, data processing, workflows, dependencies, and operating model), and build the detailed delivery blueprint that will greenlight the full-scale migration.
The work is technically rich and highly collaborative: you'll review and validate job inventories spanning hundreds of ETL workflows, define reusable migration patterns and templates, design a validation and reconciliation framework, run a proof-of-concept to stress-test the approach, and navigate client's rigorous internal governance — from Architectural Significance Assessments through Architectural Review Boards to a formal Gate 1 decision.
This is the kind of engagement where your recommendations directly shape a multi-phase, multi-million-pound programme: the target-state framework you produce here becomes the blueprint that a larger delivery team will execute against. Perfect opportunity for combining deep data engineering knowledge with architecture leadership, stakeholder influence, and structured delivery planning inside a Tier 1 financial services environment

Responsibilities:

- Agentic AI Migration Framework development — design and build an agentic AI framework to automate and accelerate migration workflowsж
- Pattern library build — develop and maintain a library of reusable migration patterns/templates for common conversion scenarios;
-Automated conversion pipeline — build pipelines that automatically convert/transform code and configurations (e.g., Matillion jobs) as part of the migration process;
-GitHub Copilot integration for code generation — integrate GitHub Copilot into the migration workflow to accelerate code generation and conversion tasks;
-Support factory pods — provide technical support, tooling, and troubleshooting to migration factory pods executing migrations at scale

Mandatory Skills Description:

- Python — strong hands-on Python development experience for building tools and automation
- GenAI/LLM integration — experience integrating GenAI/LLM capabilities into applications, workflows, or tooling
- Prompt engineering — hands-on experience designing, testing, and optimizing prompts for LLM-based tools
- AWS Bedrock — hands-on experience with AWS Bedrock for building GenAI-powered applications
- GitHub Copilot — practical experience using and/or integrating GitHub Copilot into development workflows
- Automation frameworks — experience designing and building automation frameworks/tooling from scratch
- Testing — strong experience with test automation and validation frameworks to ensure conversion accuracy
- Matillion JSON parsing — experience parsing, interpreting, and transforming Matillion job definitions (JSON format)

Nice-to-Have Skills Description:

Experience in financial domain

We're Gypsy Collective. The digital world is evolving faster than ever. New opportunities, new challenges, new ambitious goals. That’s why strong businesses need strong people.

Gypsy Collective is an exclusive talent partner for selected brands. We help our partners attract exceptional talent by building long-term relationships and becoming deeply integrated into their business, culture, and growth ambitions.

Now we're looking for a PSP Manager to take ownership of day-to-day payment operations and performance across assigned platforms, brands, streams, and GEOs. We are looking for a detail-oriented and analytical professional who can monitor payment performance, work closely with PSPs and internal teams, identify issues, and proactively improve payment stability and efficiency.
 

📅 Your daily adventures include:

• Own the day-to-day operation and performance of payment solutions across assigned platforms, streams, brands, and GEOs;
• Manage operational communication and relationships with PSPs, payment partners, aggregators, and platform representatives, including participation in discussions around commercial and operational conditions, coverage, limits, and service improvements;
• Monitor payment method availability, stability, and key performance metrics, including approval rate, decline rate, deposit success rate, Reg2Dep, and payment method conversion, and promptly respond to performance deterioration or disruptions;
• Analyze payment performance by platform, brand, GEO, provider, payment method, currency, BIN, issuer, and transaction type; identify the main causes of failed or declined transactions and implement improvements;
• Build, maintain, and optimize payment routing, cascading, fallback, and prioritization logic, including BIN-level analysis and identification of issuer-, provider-, and GEO-specific performance issues;
• Identify operational and technical bottlenecks affecting deposit and withdrawal flows and coordinate their resolution with internal teams, platforms, and external payment partners;
• Lead the integration and launch of new PSPs and payment methods, including cards, alternative payment methods, and cryptocurrency solutions, coordinating requirements, configuration, testing, launch readiness, and post-launch monitoring;
• Validate cashier functionality, payment redirects, transaction processing, payment method availability, limits, currencies, and GEO restrictions before and after launch;
• Manage payment-related tasks and incidents through Asana, Jira, platform service desks, and other applicable systems; act as the primary point of contact for operational and technical payment incidents, ensuring timely escalation and clear status updates until resolution;
• Monitor PSP performance against agreed operational expectations and initiate corrective actions when performance, stability, or service quality is insufficient;
• Cooperate with Risk & Fraud Prevention, Customer Support, VIP, Product, Retention, Technical, QA, and Analytics teams on payment-related cases and improvement initiatives, including transaction-level investigation of player payment issues;
• Maintain an up-to-date payment method matrix and payment documentation covering brands, GEOs, platforms, providers, currencies, limits, availability, provider information, error descriptions, escalation contacts, operational instructions, and troubleshooting procedures;
• Prepare regular and ad hoc payment performance reports and use dashboards, back offices, monitoring tools, and transaction reports to identify trends, incidents, provider stability issues, performance gaps, implemented improvements, and areas requiring management attention;
• Proactively recommend and implement solutions aimed at improving payment stability, scalability, customer experience, and the overall financial performance of the Company.

🧭 What makes you a great match:

• 2+ years of relevant experience as a PSP Manager or in a similar payments-focused role;
• Hands-on experience with fiat payments, bank transfers, and cryptocurrency;
• Experience with payment monitoring and analysis of approval rates and transaction performance;
• Strong analytical skills and ability to work with payment performance data;
• Experience with BI and reporting tools; Tableau is highly preferred;
• Strong attention to detail and ability to stay focused when working with large amounts of operational and payment data;
• Proactive and initiative-driven approach to work;
• Strong discipline and ability to consistently follow up on ongoing tasks and issues;
• Good communication skills and ability to collaborate with different stakeholders;
• Willingness to learn, develop, and deepen expertise in payments;
• Experience in iGaming is a plus, but not a strict requirement.
   

Benefits

💸 Flexible payment options: choose the method that works best for you;
🎁 Financial perks: Bonuses for holidays, B-day, work milestones and more - just to show we care;
📈 Learn & grow: We cover courses and certifications — and offer real opportunities to grow your career with us;
🥐 Benefit Сafeteria: Choose what suits you — sports, language courses, therapy sessions, and more;
🎉 Stay connected: From team-building events to industry conferences — we bring people together online, offline, and on stage;
💻 Modern Equipment: We provide new laptops along with essential peripherals like monitors and headphones for a comfortable workflow;
🕘 Your schedule, your rules: Start your day at 9, 10, or even 11 — we care about results, not clock-ins.

If this role sounds like a good fit for you, we’d love to hear from you — apply and tell us a bit about yourself.

This is a strategic data engineering engagement with our client to architect and plan the migration of their entire data processing and ETL estate from Matillion to AWS Glue — a foundational shift in how one of the world's largest financial market infrastructure companies handles its data pipelines.
During this Mobilisation Phase, you'll work jointly with client's engineering teams to reverse-engineer the existing landscape, design the target-state architecture across every layer (infrastructure, data processing, workflows, dependencies, and operating model), and build the detailed delivery blueprint that will greenlight the full-scale migration.
The work is technically rich and highly collaborative: you'll review and validate job inventories spanning hundreds of ETL workflows, define reusable migration patterns and templates, design a validation and reconciliation framework, run a proof-of-concept to stress-test the approach, and navigate client's rigorous internal governance — from Architectural Significance Assessments through Architectural Review Boards to a formal Gate 1 decision.
This is the kind of engagement where your recommendations directly shape a multi-phase, multi-million-pound programme: the target-state framework you produce here becomes the blueprint that a larger delivery team will execute against. Perfect opportunity for combining deep data engineering knowledge with architecture leadership, stakeholder influence, and structured delivery planning inside a Tier 1 financial services environment

• Responsibilities:

  - Design, build, and maintain ETL/ELT pipelines on AWS
  - Migrate existing data pipelines and workloads from legacy/on-prem systems to AWS
  - Develop and optimize data models for data warehouse/data lake (Redshift, S3)
  - Build and orchestrate data workflows (Glue, Step Functions, Lambda, EMR)
  - Implement data quality checks, validation, and reconciliation processes
  - Optimize pipeline performance and manage compute/storage costs
  - Ensure data security and access control (IAM, KMS, encryption)
  - Monitor and troubleshoot pipeline failures (CloudWatch, logging)
  - Collaborate with data analysts, BI developers, and architects on data requirements
  - Document data pipelines, architecture, and operational runbooks

   

• Mandatory Skills Description:

  - 5+ years of experience

  - 2 month project with posibility of extentention
  - Hands-on experience building data pipelines on AWS (Glue, EMR, Lambda, Step Functions)
  - Strong SQL and experience with data warehousing (Redshift, dimensional modeling)
  - Proficiency in Python or Scala for data engineering
  - Experience with S3-based data lake architecture (partitioning, cataloging, formats like Parquet)
  - Experience migrating data pipelines from on-prem or other cloud platforms
  - Understanding of data governance, security, and access control on AWS
  - Experience with CI/CD for data pipelines

   

• Nice-to-Have Skills Description:

  - AWS certification (Data Analytics Specialty or Data Engineer Associate)
  - Experience with streaming data (Kinesis, MSK/Kafka)
  - Familiarity with Infrastructure as Code (Terraform/CloudFormation)
  - Experience with orchestration tools (Airflow, dbt)
  - Experience in financial domain

• Languages:
  • English: C2 Proficient

Project Description:

This is a strategic data engineering engagement with our client to architect and plan the migration of their entire data processing and ETL estate from Matillion to AWS Glue — a foundational shift in how one of the world's largest financial market infrastructure companies handles its data pipelines.
During this Mobilisation Phase, you'll work jointly with engineering teams to reverse-engineer the existing landscape, design the target-state architecture across every layer (infrastructure, data processing, workflows, dependencies, and operating model), and build the detailed delivery blueprint that will greenlight the full-scale migration.
The work is technically rich and highly collaborative: you'll review and validate job inventories spanning hundreds of ETL workflows, define reusable migration patterns and templates, design a validation and reconciliation framework, run a proof-of-concept to stress-test the approach, and navigate rigorous internal governance — from Architectural Significance Assessments through Architectural Review Boards to a formal Gate 1 decision.

Responsibilities:

-Target-state architecture design — define and own the target-state AWS architecture across compute, data, and orchestration layers
-HLD/LLD ownership — produce and own High-Level Design and Low-Level Design documentation for migration workloads
-ARB submissions — prepare and present architecture proposals to the Architecture Review Board for approval
-Technical decisions — make and document key technical decisions across the migration program, balancing trade-offs (cost, performance, scalability)
Pattern definition — define reusable architecture and migration patterns for use across teams/pods
-Agentic AI framework architecture — design the architecture for the Agentic AI migration framework, including its integration with the broader technical landscape

Mandatory Skills Description:

- 5+ years experience
- hands-on experince with AWS Migration
- AWS Glue, Step Functions, Lambda, EventBridge — deep hands-on experience designing solutions using these core AWS services
- IaC (Terraform) — strong experience defining and managing infrastructure as code with Terraform
- Data platform architecture — proven experience architecting data platforms (data lakes, warehouses, pipelines) at scale
- PySpark — hands-on experience with PySpark for large-scale data processing
- CI/CD — experience designing and implementing CI/CD pipelines for infrastructure and data workflows
- AI/ML frameworks — working knowledge of AI/ML frameworks and their application within architecture design
- GitHub Copilot — practical experience using GitHub Copilot within development/architecture workflows

Nice-to-Have Skills Description:

- AWS certification (Data Analytics Specialty or Solutions Architect)
- Experience with BI tools (QuickSight, Tableau, Power BI)
- Infrastructure as Code experience (Terraform/CloudFormation)
- Industry experience relevant to your business
- Exposure to streaming data (Kinesis) or ML pipelines (SageMaker)
- experince in financial domain

Project Description:

This is a strategic data engineering engagement with our client to architect and plan the migration of their entire data processing and ETL estate from Matillion to AWS Glue — a foundational shift in how one of the world's largest financial market infrastructure companies handles its data pipelines.
During this Mobilisation Phase, you'll work jointly with engineering teams to reverse-engineer the existing landscape, design the target-state architecture across every layer (infrastructure, data processing, workflows, dependencies, and operating model), and build the detailed delivery blueprint that will greenlight the full-scale migration.
The work is technically rich and highly collaborative: you'll review and validate job inventories spanning hundreds of ETL workflows, define reusable migration patterns and templates, design a validation and reconciliation framework, run a proof-of-concept to stress-test the approach, and navigate rigorous internal governance — from Architectural Significance Assessments through Architectural Review Boards to a formal Gate 1 decision.

Responsibilities:

-Target-state architecture design — define and own the target-state AWS architecture across compute, data, and orchestration layers
-HLD/LLD ownership — produce and own High-Level Design and Low-Level Design documentation for migration workloads
-ARB submissions — prepare and present architecture proposals to the Architecture Review Board for approval
-Technical decisions — make and document key technical decisions across the migration program, balancing trade-offs (cost, performance, scalability)
Pattern definition — define reusable architecture and migration patterns for use across teams/pods
-Agentic AI framework architecture — design the architecture for the Agentic AI migration framework, including its integration with the broader technical landscape

Mandatory Skills:

AWS Database Migration Service

Mandatory Skills Description:

- 5+ years experience
- hands-on experince with AWS Migration
- AWS Glue, Step Functions, Lambda, EventBridge — deep hands-on experience designing solutions using these core AWS services
- IaC (Terraform) — strong experience defining and managing infrastructure as code with Terraform
- Data platform architecture — proven experience architecting data platforms (data lakes, warehouses, pipelines) at scale
- PySpark — hands-on experience with PySpark for large-scale data processing
- CI/CD — experience designing and implementing CI/CD pipelines for infrastructure and data workflows
- AI/ML frameworks — working knowledge of AI/ML frameworks and their application within architecture design
- GitHub Copilot — practical experience using GitHub Copilot within development/architecture workflows

Nice-to-Have Skills Description:

- AWS certification (Data Analytics Specialty or Solutions Architect)
- Experience with BI tools (QuickSight, Tableau, Power BI)
- Infrastructure as Code experience (Terraform/CloudFormation)
- Industry experience relevant to your business
- Exposure to streaming data (Kinesis) or ML pipelines (SageMaker)
- experince in financial domain

Languages:

English: C2 Proficient

Project description

This is a strategic data engineering engagement with our client to architect and plan the migration of their entire data processing and ETL estate from Matillion to AWS Glue — a foundational shift in how one of the world's largest financial market infrastructure companies handles its data pipelines.
During this Mobilisation Phase, you'll work jointly with engineering teams to reverse-engineer the existing landscape, design the target-state architecture across every layer (infrastructure, data processing, workflows, dependencies, and operating model), and build the detailed delivery blueprint that will greenlight the full-scale migration.
The work is technically rich and highly collaborative: you'll review and validate job inventories spanning hundreds of ETL workflows, define reusable migration patterns and templates, design a validation and reconciliation framework, run a proof-of-concept to stress-test the approach, and navigate rigorous internal governance — from Architectural Significance Assessments through Architectural Review Boards to a formal Gate 1 decision.

Responsibilities

-Target-state architecture design — define and own the target-state AWS architecture across compute, data, and orchestration layers

-HLD/LLD ownership — produce and own High-Level Design and Low-Level Design documentation for migration workloads

-ARB submissions — prepare and present architecture proposals to the Architecture Review Board for approval

-Technical decisions — make and document key technical decisions across the migration program, balancing trade-offs (cost, performance, scalability)

Pattern definition — define reusable architecture and migration patterns for use across teams/pods

-Agentic AI framework architecture — design the architecture for the Agentic AI migration framework, including its integration with the broader technical landscape

Skills

Must have

5+ years experience

hands-on experince with AWS Migration

AWS Glue, Step Functions, Lambda, EventBridge — deep hands-on experience designing solutions using these core AWS services

IaC (Terraform) — strong experience defining and managing infrastructure as code with Terraform

Data platform architecture — proven experience architecting data platforms (data lakes, warehouses, pipelines) at scale

PySpark — hands-on experience with PySpark for large-scale data processing

CI/CD — experience designing and implementing CI/CD pipelines for infrastructure and data workflows

AI/ML frameworks — working knowledge of AI/ML frameworks and their application within architecture design

GitHub Copilot — practical experience using GitHub Copilot within development/architecture workflows

Nice to have

AWS certification (Data Analytics Specialty or Solutions Architect)

Experience with BI tools (QuickSight, Tableau, Power BI)

Infrastructure as Code experience (Terraform/CloudFormation)

Industry experience relevant to your business

Exposure to streaming data (Kinesis) or ML pipelines (SageMaker)

experince in financial domain

Other

Languages

English: C2 Proficient

• This is a strategic data engineering engagement with our client to architect and plan the migration of their entire data processing and ETL estate from Matillion to AWS Glue — a foundational shift in how one of the world's largest financial market infrastructure companies handles its data pipelines.
  During this Mobilisation Phase, you'll work jointly with engineering teams to reverse-engineer the existing landscape, design the target-state architecture across every layer (infrastructure, data processing, workflows, dependencies, and operating model), and build the detailed delivery blueprint that will greenlight the full-scale migration.
  The work is technically rich and highly collaborative: you'll review and validate job inventories spanning hundreds of ETL workflows, define reusable migration patterns and templates, design a validation and reconciliation framework, run a proof-of-concept to stress-test the approach, and navigate rigorous internal governance — from Architectural Significance Assessments through Architectural Review Boards to a formal Gate 1 decision.

   

• Responsibilities:

  -Target-state architecture design — define and own the target-state AWS architecture across compute, data, and orchestration layers
  -HLD/LLD ownership — produce and own High-Level Design and Low-Level Design documentation for migration workloads
  -ARB submissions — prepare and present architecture proposals to the Architecture Review Board for approval
  -Technical decisions — make and document key technical decisions across the migration program, balancing trade-offs (cost, performance, scalability)
  Pattern definition — define reusable architecture and migration patterns for use across teams/pods
  -Agentic AI framework architecture — design the architecture for the Agentic AI migration framework, including its integration with the broader technical landscape

   

• Mandatory Skills Description:

  - 5+ years experience

  - 2 month project with posibility of extentention
  - hands-on experince with AWS Migration
  - AWS Glue, Step Functions, Lambda, EventBridge — deep hands-on experience designing solutions using these core AWS services
  - IaC (Terraform) — strong experience defining and managing infrastructure as code with Terraform
  - Data platform architecture — proven experience architecting data platforms (data lakes, warehouses, pipelines) at scale
  - PySpark — hands-on experience with PySpark for large-scale data processing
  - CI/CD — experience designing and implementing CI/CD pipelines for infrastructure and data workflows
  - AI/ML frameworks — working knowledge of AI/ML frameworks and their application within architecture design
  - GitHub Copilot — practical experience using GitHub Copilot within development/architecture workflows

   

• Nice-to-Have Skills Description:

  - AWS certification (Data Analytics Specialty or Solutions Architect)
  - Experience with BI tools (QuickSight, Tableau, Power BI)
  - Infrastructure as Code experience (Terraform/CloudFormation)
  - Industry experience relevant to your business
  - Exposure to streaming data (Kinesis) or ML pipelines (SageMaker)
  - experince in financial domain

   

• Languages:
  • English: C2 Proficient

WebSpellChecker is a product company that builds AI-powered text quality solutions used by engineers, businesses, and individual users worldwide. Our products help people communicate more clearly by providing spelling, grammar, and style correction across different platforms and environments. The core product is WProofreader, available as a software development kit (SDK) and browser extension that can be used as SaaS and on-premise solution.

We are currently looking for a Senior Marketing Manager to lead and elevate our marketing function. We highly value a data-driven approach and would like to hire a specialist who shares this mindset. If you are ready to transform our current gut-feel activities into systematic, measurable processes, don’t hesitate to apply!

What you will do

• Build marketing strategies and campaigns.
• Define, implement, and monitor key performance metrics regularly.
• Sharpen our value proposition and unique selling points.
• Explore and validate new market opportunities.
• Keep a close eye on competitors.
• Build and execute GTM plans for new markets or niches.
• Identify and test acquisition channels without relying on massive paid ads budgets.
• Conduct customer interviews, define our Ideal Customer Profile (ICP) and Buyer Personas.
• Analyze user journeys on our website. Find out where users drop off and fix the funnel to drive target actions.
• Collaborate closely with BizDev and Product Development teams, manage a content specialist.

Knowledge and skills required

• 4+ years in Product Marketing, Growth Marketing or related roles, with at least 3 years focused on B2B products.
• Experience working as a solo marketer or within a small team. Knowledge how to build from scratch and comfort executing with your own hands.
• Fluency in English.
• Strong data analysis skills. Deep understanding of which metrics are important and how they can be improved.
• Experience conducting customer interviews. Solid understanding of customer buying journeys and decision-making processes.
• High level of proactivity and autonomy.

Would be a plus

• Working experience with similar products.
• Experience building a marketing function from scratch.

We offer you

• Flexible schedule.
• Long-term employment.
• Assistance in professional growth through educational programs and conferences.
• Everything you need to set up a modern workstation/laptop.
• Generous number of paid days off and sick leaves.

We are looking for a Head of Product with hands-on experience in blockchain, digital asset, and/or fintech products to lead product strategy, roadmap development, and delivery.

Key Responsibilities:

• Define and maintain the product vision, strategy, and roadmap.
• Research market trends, competitors, and user needs.
• Translate business goals into clear product requirements.
• Prioritize features and manage the product backlog.
• Coordinate product, design, engineering, and business teams.
• Define product metrics and evaluate feature performance.
• Manage product delivery, timelines, risks, and dependencies.
• Work with external technology and service providers.

• Improve internal product development processes.

   

Requirements:

• Experience as a Head of Product, Product Lead, or Senior Product Manager.
• Hands-on experience with blockchain, digital asset, and/or fintech products is required.
• Strong understanding of product discovery, development, and delivery.
• Experience creating product roadmaps and writing clear requirements.
• Understanding of wallets, payments, trading systems, liquidity, custody, and KYC/AML solutions.
• Strong analytical, communication, and leadership skills.
• Experience working with technical teams and external providers.

• English proficiency sufficient for working with international teams and documentation.

   

What We Offer:

• Full-time employment.
• Remote work.
• Flexible working hours.
• Competitive compensation based on interview results.
• Paid vacation and sick leave.
• Direct influence on the product strategy and development.
• Long-term cooperation.

LoopMe is an AI company solving one of advertising's hardest problems: making brand advertising actually measurable — and making it perform. Our platform runs patented machine learning models across billions of consumer signals in real time, optimising campaigns toward outcomes like purchase intent, brand lift, and foot traffic rather than proxy metrics like clicks. The result is 2–5x better performance than industry benchmarks, at scale.

We operate a high-load programmatic infrastructure — processing millions of ad requests per second with sub-200ms response times globally. This isn't a layer on top of someone else's stack; it's built from the ground up, in-house, by the team you'd be joining. Founded in 2012 and headquartered in London, we now have 400+ people across 19 cities and have sustained 40% revenue CAGR since 2018. The engineering problems here are real, the ownership is genuine, and the scale is significant.

The opportunity

Do you want to work with patented AI technology and develop high-performance solutions? If so, we have the perfect job for you at LoopMe!

We are a global team of skilled engineers who develop and maintain real-time bidding platforms for leading advertisers worldwide. Leveraging technologies such as Java, Postgres, Clickhouse, Kafka, you will be instrumental in scaling performance, optimizing cloud infrastructure, and creating innovative features across our product portfolio. 

Our strong AI orientation extends beyond our products; we use enterprise tools like Claude Code Enterprise and Gemini Enterprise for internal automation, application development, infrastructure management, and optimization.

As the market leader in AI, LoopMe uses agile methodology to deliver product features at a fast pace. Join us and be a part of our mission to push the boundaries of what is possible in the advertising industry!

We're looking for a Software Engineer with experience designing, building and maintaining high-scale, big-data distributed systems. You'll work closely with a strong team of 16 DevOps engineers across the company to deliver a stable and highly scalable product.

What you'll do

• Collaborate on designing and setting up new features and system improvements.
• Manage and optimize cloud infrastructure on Google Cloud Platform (GCP).
• Managing, optimizing, and maintaining our diverse database ecosystem (10+ technologies).
• Designing and scaling our microservices-oriented architecture across numerous Kubernetes clusters spread across several continents.
• Update and maintain software processes and tools.
• Bring in current IT best practices to our setup.
• Work on reducing costs for the solutions we use.
• Drive automation and optimization initiatives across application development and infrastructure management using enterprise AI tools.

What you'll bring

Essential:

• 3+ years of experience in Cloud Infrastructure or Software Development.
• 3+ years of hands-on Kubernetes experience.
• 2+ years of experience with GCP, AWS, or Azure.
• Experience with scripting (Python, Bash, Go, or similar).
• Experience building and maintaining CI/CD pipelines.
• Experience with Infrastructure as Code.

Nice to have:

• Experience with high-scale distributed systems.
• Experience with Config Connector or Crossplane.
• Experience in infrastructure and cloud cost optimization.
• Knowledge of PostgreSQL administration.

What we offer

• Flexible working schedule
• 1 month of work-from-anywhere
• Annual performance bonus
• English classes
• LoopMe Gives Back
• Learning & development support

• This is a strategic data engineering engagement with our client to architect and plan the migration of their entire data processing and ETL estate from Matillion to AWS Glue — a foundational shift in how one of the world's largest financial market infrastructure companies handles its data pipelines.
  During this Mobilisation Phase, you'll work jointly with client's engineering teams to reverse-engineer the existing landscape, design the target-state architecture across every layer (infrastructure, data processing, workflows, dependencies, and operating model), and build the detailed delivery blueprint that will greenlight the full-scale migration.
  The work is technically rich and highly collaborative: you'll review and validate job inventories spanning hundreds of ETL workflows, define reusable migration patterns and templates, design a validation and reconciliation framework, run a proof-of-concept to stress-test the approach, and navigate client's rigorous internal governance — from Architectural Significance Assessments through Architectural Review Boards to a formal Gate 1 decision.
  This is the kind of engagement where your recommendations directly shape a multi-phase, multi-million-pound programme: the target-state framework you produce here becomes the blueprint that a larger delivery team will execute against. Perfect opportunity for combining deep data engineering knowledge with architecture leadership, stakeholder influence, and structured delivery planning inside a Tier 1 financial services environment

• Responsibilities:

  - Design, build, and maintain ETL/ELT pipelines on AWS
  - Migrate existing data pipelines and workloads from legacy/on-prem systems to AWS
  - Develop and optimize data models for data warehouse/data lake (Redshift, S3)
  - Build and orchestrate data workflows (Glue, Step Functions, Lambda, EMR)
  - Implement data quality checks, validation, and reconciliation processes
  - Optimize pipeline performance and manage compute/storage costs
  - Ensure data security and access control (IAM, KMS, encryption)
  - Monitor and troubleshoot pipeline failures (CloudWatch, logging)
  - Collaborate with data analysts, BI developers, and architects on data requirements
  - Document data pipelines, architecture, and operational runbooks

• Mandatory Skills Description:

  - 5+ years of experience
  - Hands-on experience building data pipelines on AWS (Glue, EMR, Lambda, Step Functions)
  - Strong SQL and experience with data warehousing (Redshift, dimensional modeling)
  - Proficiency in Python or Scala for data engineering
  - Experience with S3-based data lake architecture (partitioning, cataloging, formats like Parquet)
  - Experience migrating data pipelines from on-prem or other cloud platforms
  - Understanding of data governance, security, and access control on AWS
  - Experience with CI/CD for data pipelines

• Nice-to-Have Skills Description:

  - AWS certification (Data Analytics Specialty or Data Engineer Associate)
  - Experience with streaming data (Kinesis, MSK/Kafka)
  - Familiarity with Infrastructure as Code (Terraform/CloudFormation)
  - Experience with orchestration tools (Airflow, dbt)
  - Experience in financial domain

This is a strategic data engineering engagement with our client to architect and plan the migration of their entire data processing and ETL estate from Matillion to AWS Glue — a foundational shift in how one of the world's largest financial market infrastructure companies handles its data pipelines.
During this Mobilisation Phase, you'll work jointly with client's engineering teams to reverse-engineer the existing landscape, design the target-state architecture across every layer (infrastructure, data processing, workflows, dependencies, and operating model), and build the detailed delivery blueprint that will greenlight the full-scale migration.
The work is technically rich and highly collaborative: you'll review and validate job inventories spanning hundreds of ETL workflows, define reusable migration patterns and templates, design a validation and reconciliation framework, run a proof-of-concept to stress-test the approach, and navigate client's rigorous internal governance — from Architectural Significance Assessments through Architectural Review Boards to a formal Gate 1 decision.
This is the kind of engagement where your recommendations directly shape a multi-phase, multi-million-pound programme: the target-state framework you produce here becomes the blueprint that a larger delivery team will execute against. Perfect opportunity for combining deep data engineering knowledge with architecture leadership, stakeholder influence, and structured delivery planning inside a Tier 1 financial services environment

• Responsibilities:

  - Agentic AI Migration Framework development — design and build an agentic AI framework to automate and accelerate migration workflowsж
  - Pattern library build — develop and maintain a library of reusable migration patterns/templates for common conversion scenarios;
  -Automated conversion pipeline — build pipelines that automatically convert/transform code and configurations (e.g., Matillion jobs) as part of the migration process;
  -GitHub Copilot integration for code generation — integrate GitHub Copilot into the migration workflow to accelerate code generation and conversion tasks;
  -Support factory pods — provide technical support, tooling, and troubleshooting to migration factory pods executing migrations at scale

• Mandatory Skills Description:

  - Python — strong hands-on Python development experience for building tools and automation
  - GenAI/LLM integration — experience integrating GenAI/LLM capabilities into applications, workflows, or tooling
  - Prompt engineering — hands-on experience designing, testing, and optimizing prompts for LLM-based tools
  - AWS Bedrock — hands-on experience with AWS Bedrock for building GenAI-powered applications
  - GitHub Copilot — practical experience using and/or integrating GitHub Copilot into development workflows
  - Automation frameworks — experience designing and building automation frameworks/tooling from scratch
  - Testing — strong experience with test automation and validation frameworks to ensure conversion accuracy
  - Matillion JSON parsing — experience parsing, interpreting, and transforming Matillion job definitions (JSON format)