About Manifest Global

Manifest Global is building the infrastructure for global human capital mobility -connecting students, schools, universities, and employers across 50+ countries. Our portfolio spans Cialfo (AI-powered college counseling, 2,000+ schools), BridgeU (university guidance for international schools globally), Kaaiser (trusted study abroad counseling across India and Southeast Asia), and Explore (AI-powered university outreach, 1,000+ university partners). Together, we move talent across borders at scale. $80M raised. Still early.

About This Role

Manifest Global operates four brands across 50+ countries, generating data across thousands of schools, hundreds of thousands of students, and 1,000+ university partners. Counselor behaviour, student application journeys, university conversion rates, placement outcomes, attribution revenue - it's all there. The data exists. The question is whether the infrastructure around it is good enough to make it useful.

Right now, the data platform works. Pipelines run, the warehouse holds data, the BI layer surfaces reports. But Manifest is growing - new brands, new markets, new activation use cases - and the infrastructure needs to scale with it. There are pipelines that need to be more reliable. Transformation logic that needs to be cleaner. Warehouse design that needs to handle more volume without degrading performance. And an activation layer - reverse ETL, operational analytics, data flowing into the tools the business actually uses - that is still being built.

As a Senior Data Engineer, you will own significant parts of the data platform end to end - ingestion, transformation, warehouse, activation - and you will be one of the people who determines whether Manifest's data infrastructure is a genuine competitive advantage or a persistent constraint. You will work closely with Principal Engineers, Product, and business stakeholders across all four brands, and you will be expected to operate with the ownership and judgment of someone who has built production-grade data systems before.

What makes this role different: Manifest has real data - cross-brand, multi-geography, commercially significant data. The stack is modern: Snowflake, dbt, Hevo, Airtable, Metabase. The problems are real. And when the data infrastructure surfaces the right insight, it changes a decision that affects real students and real institutions.

AI is central to how we build: This isn't just a data engineering role - it is a role where you will actively design and build AI infrastructure that accelerates the team's own development velocity. We use Snowflake Cortex AI with Claude in our daily engineering workflow - for debugging, RCA, query optimisation, and pipeline analysis. We have already cut root cause analysis time. The next step is embedding AI deeper: automated ticket handling, intelligent monitoring, and AI-assisted development tooling that lets the team move faster without sacrificing reliability.

What You Will Own

1. AI Infrastructure for Data Engineering

• Design and build AI-assisted development tooling - LLM-powered code generation for dbt models, SQL transformations, and pipeline scaffolding that dramatically reduces time-to-production for new data assets
• Build intelligent data quality and anomaly detection systems - AI-driven monitoring that learns normal patterns across pipelines and surfaces anomalies before they propagate downstream, replacing manual threshold-based alerting
• Implement AI-augmented data cataloguing and lineage - automated documentation generation, schema understanding, and semantic tagging so engineers spend less time writing docs and more time building
• Develop AI-powered pipeline debugging and root cause analysis - tooling that diagnoses failures, traces impact through the DAG, and proposes fixes rather than requiring engineers to trace failures manually
• Build and maintain the infrastructure that supports AI features - vector stores, embedding pipelines, retrieval layers, and model serving infrastructure that powers AI capabilities across Cialfo, BridgeU, and Explore
• Evaluate and adopt emerging AI developer tools - stay ahead of how AI tooling (Claude, Cortex AI, GitHub Copilot, LLM APIs) can be embedded into the team's workflow to shorten feedback loops and accelerate feature delivery

2. Data Warehouse Design, Cost & Maintenance

• Own significant portions of the Snowflake data warehouse - schema design, performance optimisation, and the integrity of the data models that the rest of the stack depends on
• Apply strong data warehousing methodologies: dimensional modelling, layered transformation logic, clear separation between raw, staged, and served layers
• Design and build cross-brand data primitives - shared, canonical data layers for K12, Student, University, and Application data that work consistently across Cialfo, BridgeU, and Kaaiser. This is active work and a critical foundation for the multi-brand data platform
• Own Snowflake cost optimisation - monitor warehouse spend, identify high-cost queries and sync jobs, right-size warehouse configurations, and drive measurable reductions in monthly compute spend.
• Ensure the warehouse handles increasing data volumes from across all four brands without degrading query performance or downstream reliability

3. ETL/ELT Pipelines, Scheduling & Transformation Logic

• Design, build, and maintain production-grade data pipelines - ingestion via Hevo or similar, transformation via dbt, SQL-based logic that is clean, documented, and maintainable
• Design and manage Snowflake Task DAGs - build and maintain dependency-chained task graphs for ingestion, LLM processing, and sync workflows. Understand how to structure root tasks, child tasks, CRON scheduling, warehouse assignment, and failure isolation so pipelines don't cascade-fail
• Own Airtable as an operational data layer - manage Snowflake-to-Airtable and Airtable-to-Snowflake sync workflows, including the SNOWFLAKE_TO_AIRTABLE_TABLELIST sync config, upsert logic, incremental filters, and sync cost optimisation. Airtable is both a key data source and a reporting destination across brands
• Build and own reverse ETL workflows that activate warehouse data into operational tools - getting the right data into the hands of the teams that need it, not just into dashboards
• Take full ownership of pipeline failures: root cause identification, fix, downstream impact analysis, and prevention - not just resolution

4. Data Quality & Reliability

• Define and enforce data quality standards across datasets you own - automated validations, delta checks, row counts, time-based monitoring
• Build monitoring and alerting that surfaces problems before they reach the business
• Document data lineage, transformation assumptions, and technical decisions so the platform is understandable and maintainable as the team grows

5. BI Platform & Reporting

• Maintain and enhance the existing BI layer - Metabase and build reporting interfaces that non-technical stakeholders can actually use
• Collaborate with Product and Analytics teams to translate business needs into reliable technical solutions
• Communicate clearly across all four brands - be the person who can explain a data problem in business terms and a business problem in data terms

What Success Looks Like

You'll start by building a complete picture of the current state - which pipelines are fragile, where data quality is inconsistent, what the highest-impact improvements look like, and where activation use cases aren't yet built. You will have a point of view on where to move first.

From there, the infrastructure will be measurably more reliable. Pipelines that were breaking will run consistently. Data quality issues will be caught early or prevented entirely. The BI layer will be getting used - not just maintained.

Over time, the data platform will be something the business genuinely relies on - fast enough to support the pace of growth, reliable enough that data consumers trust what they are looking at, and built in a way that the next engineer who joins can understand and extend without starting from scratch.

About You

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field - or equivalent practical experience

Experience

• 5+ years building and maintaining production-grade data pipelines and data warehouses - not prototypes, but systems that real business decisions depend on
• Strong experience architecting and implementing large-scale business intelligence solutions
• Strong experience in data warehouse design and advanced SQL
• Hands-on experience with the modern data stack: Snowflake (or equivalent cloud warehouse), dbt, Hevo or Airbyte or similar
• Advanced SQL proficiency: CTEs, window functions, QUALIFY, query optimisation, and understanding the difference between SQL that works and SQL that scales
• Experience with Snowflake-native features: Task DAGs, Dynamic Tables, Snowflake Cortex AI, AI_COMPLETE, warehouse sizing, and query profiling
• Experience with Airtable as an operational data layer - syncing data between Snowflake and Airtable, managing upsert logic, and keeping sync costs low
• Experience owning Snowflake cost monitoring and optimisation - identifying expensive queries, bloated sync jobs, and warehouse over-provisioning
• Experience with user-facing BI tools: Metabase, Looker, or similar
• Experience working in agile, ticket-based workflows (Jira)
• Experience building or integrating AI/LLM tooling into data engineering workflows - specifically Snowflake Cortex AI, or LLM APIs (OpenAI, Anthropic, etc.) for structured data tasks, fuzzy matching, or pipeline automation
• Familiarity with vector databases, embedding pipelines, or retrieval-augmented generation (RAG) infrastructure is a strong plus
• Exposure to MLOps or AI infrastructure patterns - model serving, feature stores, or AI monitoring - is an advantage

Skills & Qualities

• You take ownership of reliability. When a pipeline fails, you don't just fix the immediate problem - you understand why it happened, what it affected downstream, and what needs to change so it doesn't happen again
• You communicate clearly with non-technical stakeholders. You've sat in a requirements conversation with a commercial or product team, understood what they were actually asking for, and built something that answered the real question
• You document your work well enough that someone else could maintain it - data lineage, transformation assumptions, technical decisions
• Comfortable working in a multi-brand, multi-stakeholder environment where data problems span different systems, teams, and geographies
• Strong problem-solving skills and attention to detail
• Ability to hold multiple priorities simultaneously and make good judgments about what to work on first
• You're genuinely excited about AI as a force multiplier for engineering teams - you actively use AI tools in your own workflow and have a point of view on how they can make data teams faster without sacrificing reliability

Why Manifest

We're building the infrastructure for global human capital mobility - the rails that move students, schools, universities, and employers across 50+ countries. Cialfo is in 2,000+ schools. Explore is trusted by 1,000+ universities. BridgeU runs across the UK, Europe, and the Middle East. Kaaiser has guided students across India and Southeast Asia since 1997.

The opportunity is real. $700B flows annually in remittances from migrant workers. 85M workers will be missing from developed economies by 2030. We're building the operating system that changes that.

$80M raised from Tiger Global, SIG, and Square Peg. Still early.

The team has already built the infrastructure for AI-native engineering - shared conventions, a live skills library, AI-assisted workflows across engineering, QE, product, and design. Saige is in production. Explore's AI capabilities are in production. This isn't an aspiration we're hiring you to bring to life. It's an operating system we're hiring you to extend, scale, and make permanent.

ABOUT THE ROLE

Be at the forefront of the AI revolution, working on cutting-edge projects that shape the future of financial services. You’ll join a passionate team focused on building high-quality, scalable products with real-world impact.

We’re looking for a Staff-level Backend Engineer (AI) to bridge robust backend systems with Generative AI. You’ll design the frameworks, standards, and platforms that allow AI capabilities to scale securely, reliably, and efficiently across the enterprise, going beyond feature delivery to influence long-term technical direction.

As a Staff Engineer you’ll:

• Build core services for Tide’s agentic platform, including APIs, workflow orchestration, and tool integration 
• Integrate bought components where they accelerate delivery, and build where control, trust, and reuse matter most
• Work with product, data, platform, and security teams to productionise shared AI capabilities
• Design services that are reliable, secure, observable, and easy for other teams to adopt
• Help shape reusable engineering patterns for AI-enabled workflows

WHAT WE ARE LOOKING FOR:

• Strong backend or platform engineering experience in production environments.
• Good judgement across APIs, distributed systems, cloud infrastructure, and service design.
• Experience integrating internal and third-party platforms.
• Comfort working in ambiguity and turning emerging needs into robust platform components.
• Strong focus on quality, reliability, and developer usability.
• Experience with AI infrastructure or orchestration is helpful, but not essential.
• Experience in highly regulated industries (Fintech, Healthtech, etc.) where safety and compliance are core to the product is valuable, but not essential.
• Design and build automated evaluation pipelines to measure agent reasoning accuracy and safety trajectories

Our Tech Stack:

• Java, Spring Boot and JOOQ to build the RESTful APIs of our microservices (but we welcome people who are used to any strongly typed general purpose programming language!)
• Event-driven architecture with messages over SNS+SQS and Kafka to make them reliable
• Primary datastores are MySQL and PostgreSQL via RDS or Aurora (we are heavy AWS users)
• Docker, Terraform, EKS used by the Cloud team to run the platform
• DataDog and Rollbar to keep it running
• GitHub with Sonarcloud, Semgrep and solid testing to power the CI/CD pipelines - new joiners are encouraged to have something deployed to production in their first 2 weeks
• Angular 2+ with ngrx on Web, Flutter for the Mobile App
• Fivetran/Snowflake/Looker for the BI insights and Python/Faust/Flask/Tecton + some ML libs for the automated decisioning and risk management

WHAT YOU’LL GET IN RETURN

• Competitive Compensation -  competitive salary and share options
• Time Off – Generous annual leave on top of bank holidays.
• Parental Leave – Paid maternity, paternity, and adoption leave to support your family journey.
• Sabbatical – Extended unpaid and paid leave options after completing milestone years with Tide.
• Health Insurance – Private family insurance with additional OPD coverage and top-up options.
• Life & Accident Cover – Comprehensive accidental and life insurance protection.
• Mental Wellbeing – Access to therapy sessions, courses, meditations, and workshops.
• Volunteering & Development Days – Paid days annually for volunteering or personal growth.
• Learning & Development – Annual budget for books, courses, coaching, and more.
• WOO (Work Outside the Office) – Work from abroad for up to 90 days annually.
• Home Office Setup – Contribution towards setting up your home office
• Laptop Ownership – Keep your old laptop and get a new one when it’s time for a replacement.
• Snacks & Meals – Office perks with snacks, coffee, tea, and lunch (location dependent).

TIDEAN WAYS OF WORKING

At Tide, we champion a flexible workplace model that supports both in-person and remote work to cater to the specific needs of our different teams. 

While remote work is supported, we believe in the power of face-to-face interactions to foster team spirit and collaboration. Our offices are designed as hubs for innovation and team-building, where we encourage regular in-person gatherings to foster a strong sense of community.

ABOUT THE ROLE:

Tide is hiring a Senior Staff Software Engineer to lead the architecture of our agentic platform. You will shape the shared capabilities that allow AI systems to operate safely, reliably, and at scale across Tide. That includes context, orchestration, tool execution, trust controls, observability, and evaluation. You will participate in key build versus buy decisions, integrate external components where they accelerate us, and ensure we own the parts that matter most for Tide’s trust, data advantage, and long-term platform leverage.

As a Senior Staff Engineer you’ll: 

• Define the architecture for Tide’s agentic platform
• Drive the design of shared services such as context APIs, tool layers, policy controls, and auditability 
• Partner with product, data, security, and engineering teams to turn use cases into reusable platform capabilities
• Set standards for reliability, safety, scalability, and developer experience
• Provide technical leadership across teams and unblock critical decisions
• Implement cost-management and routing logic to optimize LLM spend across different providers
• Design and build automated evaluation pipelines to measure agent reasoning accuracy and safety trajectories 

WHAT WE ARE LOOKING FOR:

• Deep experience building platform or infrastructure systems at scale
• Strong judgement across APIs, distributed systems, data, and cloud-native architecture
• Track record of leading complex cross-team technical problems
• Experience integrating third-party platforms without losing control of core architecture
• Strong understanding of reliability, security, and observability
• Experience with AI platform components is valuable, but not essential
• Experience in highly regulated industries (Fintech, Healthtech, etc.) where safety and compliance are core to the product is highly desirable 

Our Tech Stack:

• Java, Spring Boot and JOOQ to build the RESTful APIs of our microservices (but we welcome people who are used to any strongly typed general purpose programming language!)
• Event-driven architecture with messages over SNS+SQS and Kafka to make them reliable
• Primary datastores are MySQL and PostgreSQL via RDS or Aurora (we are heavy AWS users)
• Docker, Terraform, EKS used by the Cloud team to run the platform
• DataDog and Rollbar to keep it running
• GitHub with Sonarcloud, Semgrep and solid testing to power the CI/CD pipelines - new joiners are encouraged to have something deployed to production in their first 2 weeks
• Angular 2+ with ngrx on Web, Flutter for the Mobile App
• Fivetran/Snowflake/Looker for the BI insights and Python/Faust/Flask/Tecton + some ML libs for the automated decisioning and risk management

WHAT YOU’LL GET IN RETURN: 

• Competitive Compensation -  competitive salary and share options
• Time Off – Generous annual leave on top of bank holidays.
• Parental Leave – Paid maternity, paternity, and adoption leave to support your family journey.
• Sabbatical – Extended unpaid and paid leave options after completing milestone years with Tide.
• Health Insurance – Private family insurance with additional OPD coverage and top-up options.
• Life & Accident Cover – Comprehensive accidental and life insurance protection.
• Mental Wellbeing – Access to therapy sessions, courses, meditations, and workshops.
• Volunteering & Development Days – Paid days annually for volunteering or personal growth.
• Learning & Development – Annual budget for books, courses, coaching, and more.
• WOO (Work Outside the Office) – Work from abroad for up to 90 days annually.
• Home Office Setup – Contribution towards setting up your home office
• Laptop Ownership – Keep your old laptop and get a new one when it’s time for a replacement.
• Snacks & Meals – Office perks with snacks, coffee, tea, and lunch (location dependent).

TIDEAN WAYS OF WORKING

At Tide, we champion a flexible workplace model that supports both in-person and remote work to cater to the specific needs of our different teams. 

While remote work is supported, we believe in the power of face-to-face interactions to foster team spirit and collaboration. Our offices are designed as hubs for innovation and team-building, where we encourage regular in-person gatherings to foster a strong sense of community.

Who We Are

Konrad is a next generation digital consultancy. We are dedicated to solving complex business problems for our global clients with creative and forward-thinking solutions. Our employees enjoy a culture built on innovation and a commitment to creating best-in-class digital products in use by hundreds of millions of consumers around the world. We hire exceptionally smart, analytical, and hard working people who are lifelong learners.

About The Role

As a Senior Data Engineer you’ll be tasked with designing, building, and maintaining scalable data platforms and pipelines. Your deep knowledge of data platforms such as Azure Fabric, Databricks, and Snowflake will be essential as you collaborate closely with data analysts, scientists, and other engineers to ensure reliable, secure, and efficient data solutions.

What You’ll Do

• • Design, build, and manage robust data pipelines and data architectures.
  • Implement solutions leveraging platforms such as Azure Fabric, Databricks, and Snowflake.
  • Optimize data workflows, ensuring reliability, scalability, and performance.
  • Collaborate with internal stakeholders to understand data needs and deliver tailored solutions.
  • Ensure data security and compliance with industry standards and best practices.
  • Perform data modelling, data extraction, transformation, and loading (ETL/ELT).
  • Identify and recommend innovative solutions to enhance data quality and analytics capabilities.

Qualifications

• Bachelor’s degree or higher in Computer Science, Data Engineering, Information Technology, or a related field.
• 5+ years of professional experience as a Data Engineer or similar role.
• Proficiency in data platforms such as Azure Fabric, Databricks, and Snowflake.
• Hands-on experience with data pipeline tools, cloud services, and storage solutions.
• Strong programming skills in SQL, Python, or related languages.
• Experience with big data technologies and concepts (Spark, Hadoop, Kafka).
• Excellent analytical, troubleshooting, and problem-solving skills.
• Ability to effectively communicate technical concepts clearly to non-technical stakeholders.

Nice to have

• Certifications related to Azure Data Engineering, Databricks, or Snowflake.
• Familiarity with DevOps practices and CI/CD pipelines

Konrad is committed to maintaining a diverse work environment and is proud to be an equal opportunity employer. All qualified applicants, regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status will receive consideration for employment. If you have any accessibility requirements or concerns regarding the hiring process or employment with us, please notify us so we can provide suitable accommodation.

While we sincerely appreciate all applications, only those candidates selected for an interview will be contacted.

#LI-Hybrid

Who We Are

Konrad is a next generation digital consultancy. We are dedicated to solving complex business problems for our global clients with creative and forward-thinking solutions. Our employees enjoy a culture built on innovation and a commitment to creating best-in-class digital products in use by hundreds of millions of consumers around the world. We hire exceptionally smart, analytical, and hard working people who are lifelong learners.

About The Role

As a Data Engineer you’ll be tasked with designing, building, and maintaining scalable data platforms and pipelines. Your deep knowledge of data platforms such as Azure Fabric, Databricks, and Snowflake will be essential as you collaborate closely with data analysts, scientists, and other engineers to ensure reliable, secure, and efficient data solutions.

What You’ll Do

• Design, build, and manage robust data pipelines and data architectures.
• Implement solutions leveraging platforms such as Azure Fabric, Databricks, and Snowflake.
• Optimize data workflows, ensuring reliability, scalability, and performance.
• Collaborate with internal stakeholders to understand data needs and deliver tailored solutions.
• Ensure data security and compliance with industry standards and best practices.
• Perform data modelling, data extraction, transformation, and loading (ETL/ELT).
• Identify and recommend innovative solutions to enhance data quality and analytics capabilities.

Qualifications

• Bachelor’s degree or higher in Computer Science, Data Engineering, Information Technology, or a related field.
• At least 3 years of professional experience as a Data Engineer or similar role.
• Proficiency in data platforms such as Azure Fabric, Databricks, and Snowflake.
• Hands-on experience with data pipeline tools, cloud services, and storage solutions.
• Strong programming skills in SQL, Python, or related languages.
• Experience with big data technologies and concepts (Spark, Hadoop, Kafka).
• Excellent analytical, troubleshooting, and problem-solving skills.
• Ability to effectively communicate technical concepts clearly to non-technical stakeholders.

Nice to have

• Certifications related to Azure Data Engineering, Databricks, or Snowflake.
• Familiarity with DevOps practices and CI/CD pipelines.

Perks and Benefits

• Socials, Outings & Retreats
• One day per week Work From Home flexibility
• Subsidized Lunch
• Culture of Learning & Development

Konrad is committed to maintaining a diverse work environment and is proud to be an equal opportunity employer. All qualified applicants, regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status will receive consideration for employment. If you have any accessibility requirements or concerns regarding the hiring process or employment with us, please notify us so we can provide suitable accommodation.

While we sincerely appreciate all applications, only those candidates selected for an interview will be contacted.

We are hiring across multiple locations

India: Hyderabad, Delhi NCR, Bengaluru
Europe: London, Serbia, Sofia, Lithuania, Berlin

We are hiring across multiple locations

India: Hyderabad, Delhi NCR, Bengaluru
Europe: London, Serbia, Sofia, Lithuania, Berlin

ABOUT THE ROLE

Be at the forefront of the AI revolution, working on cutting-edge projects that shape the future of financial services. You’ll join a passionate team focused on building high-quality, scalable products with real-world impact.

We’re looking for a Staff-level Backend Engineer (AI) to bridge robust backend systems with Generative AI. You’ll design the frameworks, standards, and platforms that allow AI capabilities to scale securely, reliably, and efficiently across the enterprise, going beyond feature delivery to influence long-term technical direction.

As a Staff Engineer you’ll:

• Build core services for Tide’s agentic platform, including APIs, workflow orchestration, and tool integration 
• Integrate bought components where they accelerate delivery, and build where control, trust, and reuse matter most
• Work with product, data, platform, and security teams to productionise shared AI capabilities
• Design services that are reliable, secure, observable, and easy for other teams to adopt
• Help shape reusable engineering patterns for AI-enabled workflows

WHAT WE ARE LOOKING FOR:

• Strong backend or platform engineering experience in production environments.
• Good judgement across APIs, distributed systems, cloud infrastructure, and service design.
• Experience integrating internal and third-party platforms.
• Comfort working in ambiguity and turning emerging needs into robust platform components.
• Strong focus on quality, reliability, and developer usability.
• Experience with AI infrastructure or orchestration is helpful, but not essential.
• Experience in highly regulated industries (Fintech, Healthtech, etc.) where safety and compliance are core to the product is valuable, but not essential.
• Design and build automated evaluation pipelines to measure agent reasoning accuracy and safety trajectories

Our Tech Stack:

• Java, Spring Boot and JOOQ to build the RESTful APIs of our microservices (but we welcome people who are used to any strongly typed general purpose programming language!)
• Event-driven architecture with messages over SNS+SQS and Kafka to make them reliable
• Primary datastores are MySQL and PostgreSQL via RDS or Aurora (we are heavy AWS users)
• Docker, Terraform, EKS used by the Cloud team to run the platform
• DataDog and Rollbar to keep it running
• GitHub with Sonarcloud, Semgrep and solid testing to power the CI/CD pipelines - new joiners are encouraged to have something deployed to production in their first 2 weeks
• Angular 2+ with ngrx on Web, Flutter for the Mobile App
• Fivetran/Snowflake/Looker for the BI insights and Python/Faust/Flask/Tecton + some ML libs for the automated decisioning and risk management