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.

TITLE: Cotton & Blends Production Manager

RESPONSIBILITIES:

Fiber Inventory & Quality Control

• Oversee Cotton & Blends fiber inventory levels to ensure adequate supply for spinning schedules while minimizing waste and overstock.
• Inspect and verify that only quality fiber—meeting specified micron, length, and color consistency standards—is released into the spinning process.
• Implement checkpoints to catch non-conforming fiber before production begins, preventing downstream defects.
• Coordinate with sourcing and warehouse teams to maintain accurate inventory records and proper storage conditions for raw Cotton & Blends.

On-Time Delivery (OTD) Management

• Own fiber OTD performance, tracking delivery timelines from suppliers to spinning mills and flagging potential delays.
• Proactively manage production schedules to ensure fiber is available when needed, communicating risks to cross-functional partners.
• Resolve supply interruptions by expediting shipments or reallocating inventory as necessary to meet production deadlines.
• Establish and monitor key performance indicators (KPIs) for supplier lead times and delivery reliability.

Spinning & Production Support

• Partner with spinning mills to ensure fiber lots are processed according to technical specifications and quality expectations.
• Monitor fiber consumption during spinning to identify discrepancies, yield loss, or quality deviations.
• Work upstream with suppliers to align fiber bale composition, lot sizing, and traceability for smoother mill integration.
• Maintain clear documentation of fiber lots, test results, and production flow to support traceability and continuous improvement.

Cross-Functional Collaboration

• Coordinate with planners and production team to align fiber availability with production demand and spinning schedules.
• Collaborate with R&D, Product Development, and Sourcing teams to support seamless production handoffs.
• Provide input on fiber purchasing decisions based on production capacity, lead times, and quality performance history.
• Escalate production blockers (e.g., fiber shortages, quality holds) with recommended solutions to meet OTD goals.

QUALIFICATIONS

• Education: Degree in Textile Engineering, Material Science, Supply Chain, or a related field.
• Production Experience: Proven experience managing raw materials in a textile or apparel production environment, preferably with Cotton & Blends or other luxury fibers.
• Quality Focus: Strong ability to assess fiber quality and enforce standards before spinning.
• Inventory & OTD Acumen: Demonstrated skill in tracking inventory levels and driving on-time delivery performance.
• Analytical Skills: Ability to use data to monitor fiber usage, identify yield issues, and improve production flow.
• Collaboration: Experience working with spinning mills, suppliers, planners, and internal production teams to resolve issues quickly.

Preferred:

• Experience with Cotton & Blends fiber grading, testing, or lot management.
• Knowledge of spinning mill operations and fiber-to-yarn conversion.
• Familiarity with inventory management systems or ERP tools.
• Understanding of sustainable fiber sourcing and production practices.

ABOUT THE ROLE

The Manager – Digital Transformation, Utilities will serve as the central coordination and execution member for advancing digitalization across distribution utilities within the Grids of the Future portfolio. This is a high-impact, cross-functional role that bridges strategic programme delivery, stakeholder engagement, technology deployment, and institutional capacity building. The incumbent will work closely with distribution companies (DISCOMs), grid operators, government energy ministries, multilateral institutions, technology vendors, and civil society organisations to drive measurable transformation outcomes at scale.

The role demands equal command of sector-specific technical knowledge — particularly in distribution utility operations, grid modernisation, software engineering, and energy data infrastructure — and of the human and organisational dimensions of large-scale digital change. The successful candidate will be equally comfortable presenting a roadmap to a utility board, reviewing a technical architecture with an engineering team, negotiating a data-sharing protocol with a regulator, and steering a cross-vendor delivery sprint.

KEY RESPONSIBILITIES

Digital Transformation Strategy and Programme Delivery

• Lead the design and execution of multi-year digital transformation roadmaps for distribution utilities, covering smart metering (AMI/AMR), SCADA/DMS upgrades, outage management systems (OMS), and integrated asset management platforms.
• Develop programme charters, milestone frameworks, KPI dashboards, and risk registers aligned with organisational priorities and donor/funder reporting requirements.
• Translate high-level transformation mandates into actionable work plans with clear ownership, resource allocation, and dependency mapping across technology, operations, and regulatory workstreams.
• Track and report programme progress to senior leadership, boards, and international stakeholders; prepare Board-ready briefings, donor reports, and policy submissions.
• Manage budget cycles, procurement processes, and contract oversight for digital initiatives, including vendor selection, SoW review, and performance monitoring.

Distribution Utility and Grid Digitalisation

• Provide technical advisory and implementation support to distribution utilities on grid digitalisation: smart grid architecture, IoT sensor deployment, SCADA integration, geographic information systems (GIS), and field force automation.
• Advise on regulatory and commercial frameworks for digital utilities: cost-of-service tariff mechanisms, regulatory asset base treatment of digital capex, and benchmarking against international best practice (EU DSO model, India RDSS, African utility digitalisation programmes).
• Support utilities in adopting advanced metering infrastructure (AMI), prepaid metering, distributed energy resource management systems (DERMS), and virtual power plant (VPP) frameworks.
• Facilitate utility-level data governance frameworks — meter data management systems (MDMS), data lakes, and secure data exchange protocols — in compliance with applicable data protection law including the India DPDP Act 2023.
• Assess AT&C loss reduction opportunities through digital interventions including smart billing, automated fault detection, and AI-powered loss analytics.

Software Engineering Oversight and Technology Delivery

• Engage directly with engineering teams — internal and vendor-side — on software architecture, integration design, API specifications, and release planning for utility digital products.
• Oversee technical delivery of software products, platforms, and integrations: sprint governance, code quality standards, DevOps/CI-CD pipeline management, and technical debt prioritisation.
• Review and provide input on system design documents, technical specifications, and vendor software proposals; ensure proposed solutions are robust, scalable, and fit for utility operating environments.
• Bridge the gap between business requirements from utility stakeholders and engineering execution, ensuring technical teams have clear, well-specified backlogs and utility counterparts understand delivery constraints.
• Evaluate build vs buy vs configure decisions for utility digital components and guide procurement accordingly.

Big Data, AI and Advanced Analytics

• Oversee the design and deployment of big data infrastructure for utilities: data pipelines from smart meters, SCADA systems, weather APIs, and demand-response platforms into centralised analytics environments.
• Champion the use of AI/ML models for demand forecasting, predictive maintenance, fault detection and classification, energy theft detection, and customer segmentation.
• Evaluate and onboard AI product vendors, conducting technical due diligence on model performance, data infrastructure requirements, integration APIs, and explainability standards.
• Establish model governance protocols including data quality standards, bias audits, retraining schedules, and version control to ensure trustworthy AI deployment in critical infrastructure.
• Build internal capability through training programmes, Centre of Excellence frameworks, and knowledge management platforms so that utilities can eventually self-sustain AI-driven operations.

Change Management and Organisational Transformation

• Design and lead structured change management programmes using established frameworks (Prosci ADKAR, Kotter 8-Step, or equivalent) to drive adoption of digital systems within utility workforce structures.
• Conduct stakeholder mapping, change readiness assessments, and impact analyses for each transformation initiative; develop communication and engagement plans for different audience segments.
• Partner with utility HR and L&D functions to design digital skilling curricula for field engineers, billing teams, control room operators, and senior management.
• Manage change fatigue and resistance in large bureaucratic organisations; coach utility leadership on digital culture and agile ways of working.
• Track adoption metrics, benefits realisation, and behavioural change indicators alongside technical deployment milestones.

Ecosystem Coordination and Stakeholder Engagement

• Serve as the primary relationship manager for technology companies, solution providers, system integrators, and platform vendors operating in the utility digital space.
• Coordinate with government bodies (Ministry of Power, CERC/SERCs, BEE, ISA, IRENA, SEforALL, and comparable regional bodies) on policy alignment, regulatory sandbox proposals, and joint programme design.
• Represent GEAPP's Grids of the Future team at industry forums, utility roundtables, and international energy conferences; build and maintain a professional network across the utility digital ecosystem.
• Facilitate consortium arrangements between utilities, technology providers, and financiers for large-scale digital infrastructure deployments.
• Support knowledge-exchange partnerships with peer organisations, development finance institutions (AfDB, ADB, WB, IFC), and bilateral aid agencies engaged in utility digitalisation.

Monitoring, Evaluation and Learning

• Design and operationalise MEL frameworks for digital transformation programmes, including theory-of-change mapping, logframe development, and results measurement.
• Oversee collection, validation, and analysis of programme data; produce periodic performance reports and impact assessments for internal governance and external accountability.
• Embed continuous improvement cycles including retrospectives, lessons-learned documentation, and adaptive management into programme delivery processes.

REQUIREMENTS

Education

• Bachelor's degree (mandatory) in Electrical Engineering, Computer Science, Software Engineering, Information Systems, or a related technical field.
• Master's degree (strongly preferred) in Energy Systems, Technology Management, MBA, Public Policy, or equivalent.
• Relevant certifications (desirable): PMP / PgMP, PRINCE2, Prosci Change Management, AWS/GCP/Azure Data, SAFe Agile, TOGAF, or utility-specific credentials such as IEEE Smart Grid certifications.

Professional Experience

• Minimum 7–9 years of progressive experience spanning software engineering, digital transformation, and programme management, with at least 3 years directly in the energy or utilities sector.
• Demonstrated track record of successfully managing end-to-end digital transformation programmes from concept through commissioning — ideally within a distribution utility, energy ministry, multilateral organisation, or consulting firm serving these clients.
• Hands-on software engineering background: experience in designing, building, or overseeing development of enterprise-grade software products, APIs, data platforms, or utility-facing applications, with the ability to engage credibly with engineering teams on architecture, code quality, and delivery.
• Hands-on experience with distribution utility operations: understanding of T&D network operations, OMS/DMS/EMS/GIS systems, meter-to-cash processes, and commercial billing systems.
• Experience working with or within a DISCOM, state power utility, or equivalent regulated energy entity is strongly preferred.
• Prior exposure to climate finance, green energy, or international development programming is advantageous.
• Must be based in New Delhi or willing and able to relocate to New Delhi prior to joining. The role involves regular in-person engagement with government bodies, utility leadership, and partners in the National Capital Region.

Technical & Sector Knowledge

• Digital Transformation

  • End-to-end transformation architecture: technology assessment, solution design, vendor management, and change delivery.
  • Digital maturity modelling and diagnostic frameworks for utilities.
  • Experience deploying at least two of: AMI, SCADA/DMS, ERP (SAP IS-U or Oracle CC&B), GIS, field force automation, or customer self-service portals.

  Software Engineering

  • Solid foundation in software engineering principles: system design, APIs, microservices architecture, DevOps/CI-CD pipelines, and cloud-native development.
  • Proficiency in at least one backend language (Python, Java, Node.js, or equivalent) and familiarity with frontend frameworks sufficient to review and guide development teams.
  • Experience managing or working alongside engineering squads: sprint planning, code review culture, technical debt management, and release governance.
  • Hands-on exposure to building or integrating utility-facing software such as billing systems, MDMS, mobile field force apps, consumer portals, or grid management dashboards.
  • Ability to evaluate vendor software on technical merit by reviewing architecture diagrams, integration specs, and API documentation without relying solely on vendor claims.

  Programme and Project Management

  • Strong command of PM methodologies: Waterfall, Agile/Scrum, and hybrid approaches.
  • Experience managing multi-workstream, multi-stakeholder programmes with budgets exceeding USD 2 million.
  • Proficiency in PM tools such as MS Project, Jira, Smartsheet, or Asana.
  • Risk management, issue escalation, and executive reporting across complex programme portfolios.

  Change Management

  • Structured change management methodology (ADKAR, Kotter, or equivalent) applied to technology adoption in large organisations.
  • Communication planning, training design, and benefits realisation tracking.
  • Experience managing union-heavy or government-owned utility environments preferred.

  Big Data and Data Engineering

  • Understanding of data pipeline architecture: ingestion, storage (data lake/warehouse), transformation, and visualisation layers.
  • Familiarity with AMI/MDMS data flows, time-series energy data, and GIS data integration.
  • Exposure to cloud data platforms (AWS S3/Glue/Redshift, GCP BigQuery, Azure Synapse) and BI tools such as Power BI, Tableau, or Looker.
  • Data governance: data dictionaries, data quality management, and master data management in a utility context.

  AI and Machine Learning Products

  • Working knowledge of AI/ML application areas for utilities: demand forecasting, predictive maintenance, energy theft detection, fault classification, and customer analytics.
  • Ability to evaluate AI vendor proposals including model performance metrics, training data requirements, integration feasibility, and explainability.
  • Experience establishing or contributing to an AI governance or model risk framework.
  • Familiarity with LLMs and generative AI use cases relevant to utility back-office and field operations.

  Distribution Utility Domain Knowledge

  • Deep understanding of the distribution utility value chain: generation procurement, transmission interface, distribution network operations, commercial metering, billing, and consumer interface.
  • Familiarity with AT&C loss reduction programmes, RDSS (India), or comparable international grid investment frameworks.
  • Understanding of DER integration challenges: rooftop solar, EV charging load management, net metering, and DERMS deployment.

  Stakeholder and Partner Coordination

  • Ability to manage diverse, cross-sector stakeholder ecosystems: regulators, utilities, government ministries, technology vendors, financiers, and civil society.
  • Experience structuring and managing partnerships, MoUs, data-sharing agreements, and consortium arrangements.
  • Comfort engaging at senior leadership, board, and ministerial levels as well as at technical working-group level.

  Additional Desirable Skills and Attributes

  • Knowledge of regulatory structures: tariff orders, CERC/SERC proceedings (India), or equivalent national regulatory frameworks in other jurisdictions.
  • Cybersecurity awareness for OT/IT convergence environments: IEC 62351, NERC CIP standards, and secure communications for SCADA and AMI networks.
  • Understanding of climate finance instruments relevant to utility infrastructure: concessional loans, green bonds, results-based financing, and blended finance structures.
  • Experience with international development organisations (World Bank, ADB, USAID, GIZ, FCDO) and their programme design and reporting norms.
  • Familiarity with ISO 55000 (Asset Management) in the context of utility digitalisation.
  • Knowledge of open-source platforms relevant to energy: OpenADR, OpenDSS, FIWARE, or OSCP for EV/charging management.
  • Experience with regulatory sandbox design or innovation facilitation in regulated utility environments.
  • Prior experience as a CTO, VP Engineering, or Head of Digital in an energy sector organisation is a strong differentiator.
  • Multilingual capability is an advantage, particularly Hindi or other languages relevant to GEA's programme geographies.

Skills & Competencies

• Systems Thinking: Ability to see technical, commercial, and institutional dimensions of utility transformation as an integrated whole; designs solutions that address root causes rather than symptoms.

  Influence Without Authority: Achieves alignment and action across government bodies, utility management, and vendor partners without direct reporting lines.

  Adaptive Leadership: Navigates ambiguity in complex, politically sensitive environments; adjusts approach based on stakeholder dynamics and evolving programme context.

  Data-Driven Decision Making: Defaults to evidence and quantitative analysis while remaining sensitive to qualitative and contextual factors that shape utility organisations.

  Communication Excellence: Translates technical complexity into clear, compelling narratives for non-technical audiences; equally effective in boardrooms, field visits, and policy forums.

  Delivery Orientation: Strong bias for action and accountability; builds structured tracking mechanisms and holds self and others to agreed milestones and standards.

  Collaboration and Inclusion: Builds high-performing cross-functional teams; actively includes diverse perspectives from utility field staff to senior ministry officials.

Work Environment and Travel

• Primary base: New Delhi, India. Candidates must be based in or willing to relocate to New Delhi before joining.
• Regular in-person engagement with government ministries (Ministry of Power, MNRE), DISCOMs, and NCR-based partners is integral to the role.
• Hybrid work arrangement; significant presence at utility sites, government offices, and partner locations required.
• Domestic and international travel expected at 30–40% annually, including visits to utility field sites, state capitals etc.
• Must be comfortable working across time zones to coordinate with multilateral partners, development banks, and government counterparts.
• Professional development allowance for certifications, conferences, and executive education

Data Engineer with experience working with GCP wanted to join us on a permanent basis. You can either join us in our growing Mumbai team or join us remotely from across India. 

Step into the Koppling workstream as a Data Engineer and be a key player in building a sophisticated media data warehouse. Your role will involve developing and deploying robust ETL/ELT data pipelines to automate the integration of 3rd party data sources at scale. This is an excellent opportunity to apply solid technical problem-solving skills, advance your data engineering capabilities, and gain a foundational understanding of the marketing data domain. You'll contribute to creating a centralized, reliable data source that informs critical business decisions, working within a collaborative team environment.

What you’ll be doing

• Developing, and deploying robust ETL/ELT data pipelines using Python and SQL to integrate various 3rd party data sources.
• Automating the integration of 3rd party data sources at scale, ensuring data accuracy and timeliness for our media data warehouse.
• Utilizing Google Cloud Platform (GCP) services such as BigQuery, Cloud Run, and Scheduler for efficient data processing and orchestration.
• Performing data modeling and transformations using dbt and SQL to structure and refine data within the media data warehouse.
• Managing and version controlling pipeline code and configurations using Git, ensuring collaborative development and deployment.
• Troubleshooting and optimizing existing data pipelines to enhance reliability, performance, and scalability.
• Applying infrastructure-as-code principles to manage data resources, potentially using tools like Terraform for environment provisioning.
• Developing or integrating APIs for complex data ingestion and exploring the use of streaming data technologies like Kafka or Pub/Sub for real-time data needs.
• Implementing and maintaining CI/CD pipelines to automate the testing, deployment, and monitoring of data solutions.

What we want from you

• Professional experience in data engineering or a similar role.
• Hands-on experience with Google Cloud Platform (GCP) services including BigQuery, Cloud Run, and Scheduler.
• Proficiency in SQL for data manipulation and analysis.
• Strong programming skills in Python.
• Experience with dbt.
• Familiarity with infrastructure-as-code principles.
• Understanding of data warehousing concepts, ETL/ELT processes, and data modeling.
• Experience with version control systems (e.g., Git).
• Excellent problem-solving skills, attention to detail, and a proactive attitude.
• Ability to work independently and as part of a team in a fast-paced environment.

Desirable Attributes

• Familiarity with Terraform.
• Experience with API Development.
• Knowledge of streaming data processing concepts (e.g., Kafka, Pub/Sub).
• Familiarity with CI/CD pipelines.
• Relevant GCP certifications are a plus.

What we can offer you

Alongside the opportunity to work with some of the most exciting brands around the world, we’ll also prioritise your career development and help you grow your skills. We’ll empower you to make a difference, allow you to be yourself, and respect who you are.

Our culture thrives on our core values, designed for impact-driven individuals: Heart, Brains and Courage.

We lead with Heart, fostering empathy and trust where genuine connections and human-centric work flourish.
We empower your Brains for innovation, valuing relentless curiosity and collaborative intelligence to solve complex challenges.
And we champion Courage, inspiring you to speak up, embrace experimentation, and advocate for bold solutions that push our thinking to be better than yesterday.

AT VML Enterprise Solutions

Our Enterprise Solutions division houses strategic consultants, creative and technical architects and skilled developers and operators that together help some of the world’s leading organisations to deliver outstanding digital experiences across all major routes to market worldwide: marketplaces, online retailers, D2C, B2B and social platforms. With over 4,200 experts in 55 operational centres across 34 countries, our capabilities span the entire buying journey from customer acquisition, through engagement, to conversion and loyalty, driving multi-channel growth for world-leading brands.

We work with some of the most exciting brands such as The Coca-Cola Company, EY, Bosch, Unilever, Ford, DFS, Mercedes-Benz, Johnson & Johnson, Nestlé, Sainsbury’s, Selfridges, Shell and Tiffany & Co. We’ve built over 500 platforms for brands and retailers and generate in excess of $29bn annually for our clients and work with over 50 strategic partners including Adobe, SAP, Salesforce, HCL, Shopify, Sitecore, BigCommerce, commerce tools and Acquia. Our reputation is based on our people, and we believe we have some of the best in the business.

As our business grows internationally, we’re looking for new people to join us on our journey to inspire and take a key role in shaping some of the best commerce solutions, services, and websites in the world. Working as a team, no problem is insurmountable; we share in our client’s successes and believe that anyone can show creative bravery no matter what their role is in the team.

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