Travco Group is hiring a Senior Data Engineer to build the group's unified cloud data platform for analytics, AI and machine learning. Founded in 1979, Travco is one of the region's largest integrated travel and tourism groups. It spans destination management, hotels, resorts and Nile cruises, transport, aviation services and real estate.

You will be the technical lead for data engineering across the group. You will bring together data from Travco's companies (hotels and cruises, destination management, transport, marketing, finance and guest systems) into one governed platform on Google Cloud. That platform will feed reporting, analytics and AI applications across business units.

You will also evaluate emerging AI and data technologies and recommend which ones the group should adopt. You will make design decisions on complex, non-standard data requests from business teams.

Location: Bangalore / remote

Experience: 5+ years

Key responsibilities

Data platform and pipelines (GCP)

- Design, build and own production data pipelines on Google Cloud: BigQuery, Cloud Storage, Pub/Sub, Dataflow, Cloud Run and Cloud Functions.
- Orchestrate batch and near-real-time workloads with Cloud Composer (Airflow), Workflows or an equivalent tool.
- Model data in BigQuery with dbt or Dataform. Build dimensional models and analytics-ready marts.
- Own BigQuery cost and performance: partitioning, clustering, slot vs on-demand pricing, and query optimisation.
- Use infrastructure-as-code (Terraform) and CI/CD for all data deployments.

Oracle OPERA integration

- Build and maintain reliable ingestion from Oracle OPERA PMS. This covers reservations, stays, profiles, rates, revenue, folios and inventory across all hotel and Nile cruise properties.
- Integrate through the Oracle Hospitality Integration Platform (OHIP) APIs for OPERA Cloud, or through direct Oracle database extraction for on-premise OPERA, as the workplace requires.
- Handle incremental loads and change data capture from OPERA, including late-arriving changes, cancellations and reinstatements.
- Map OPERA codes (market, source, rate and room-type codes) into consistent group-wide definitions.

Unifying other sources

- Integrate destination management and tour operating systems (reservations, contracting, transfers, excursions), B2B tour operator and partner feeds,



transport fleet data, the booking engine, channel manager, GA4 BigQuery export, ad platforms (Google Ads, Meta), CRM, guest accounts, ERP and finance.
- Build custom API connectors where managed connectors don't exist. Handle rate limits, pagination, retries and schema changes.
- Build and maintain a unified guest identity: one record across OPERA profiles, DMC bookings, web bookings, CRM and the loyalty programme, so a guest who books a package, stays at a hotel and takes a Nile cruise is recognised as one customer.

AI-ready data

- Build and maintain retrieval infrastructure: embeddings, chunking, and vector search (BigQuery vector search, Vertex AI).
- Expose governed data to AI applications and agents through APIs, MCP servers and a semantic layer of defined metrics.
- Partner with AI and analytics colleagues on data preparation for advanced analytics & GenAI use cases.

Governance, quality and operations

- Implement data quality tests, freshness monitoring, schema contracts and alerting, so issues are caught by systems before they reach users.
- Apply privacy and security controls: PII classification, column-level security, pseudonymisation, consent propagation, and retention policies.
- Ensure compliance with GDPR other applicable regulations in the group's operating and source markets, including the EU and the GCC.
- Maintain documentation, lineage and a data catalogue so every metric can be traced to its source.
- Provide production support and incident resolution for the data platform.

Leadership and collaboration

- Work with group companies and their revenue, sales, marketing, finance and operations to gather requirements, agree shared definitions and secure data access.
- Manage deliverables from external vendors and service providers.

Required qualifications
- 5+ years of hands-on experience building production data pipelines and data platforms.
- 2+ years owning delivery of data pipelines on a major cloud platform.



GCP and BigQuery preferred; Snowflake, AWS or Azure accepted with willingness to work on GCP.
- Expert SQL and production-grade Python: tested, version-controlled and reviewed code.
- Hands-on experience extracting data from Oracle databases or Oracle Hospitality OPERA, or from comparable enterprise operational systems.
- Strong data modelling skills: dimensional modelling, slowly changing dimensions, and incremental/CDC loading patterns.
- Experience with dbt or Dataform, and with an orchestration tool such as Airflow.
- Experience building integrations against REST APIs and handling messy file-based sources (SFTP, CSV, XML).
- Working knowledge of data governance, privacy and data quality practices, including handling personal data.
- Clear communication with non-technical stakeholders, in English.
- Bachelor's degree in computer science, engineering, information systems or a related field, or equivalent practical experience.

Preferred qualifications
- Experience in travel and hospitality data: PMS, CRS, booking engines, channel managers, DMC or tour operator reservation systems, and commercial concepts (ADR, RevPAR, room nights, pickup, OTA vs direct, B2B allotments).
- Direct experience with OHIP APIs, OPERA Cloud or OPERA 5 data structures.
- Experience with marketing data: GA4 BigQuery export, Google Ads and Meta APIs, server-side tracking data.
- Experience building LLM-based extraction pipelines, RAG systems, or vector search in production.
- Familiarity with Vertex AI, Gemini in BigQuery, or comparable cloud AI services.
- Experience building identity resolution or customer data platform (CDP) capabilities.
- Google Cloud Professional Data Engineer certification.

Core competencies
- Ownership: takes a problem from source system to production pipeline without needing a ticket for every step.
- Technical judgement: chooses tools for clear reasons, weighing cost, maintainability and team size.
- Collaboration: builds trust with departments that own the data, and negotiates access constructively.
- Developing others: shares knowledge, reviews code, and raises the standards of the people around them.
- Continuous learning: keeps up with data and AI tooling, and applies new methods where they solve a real problem.

📌 Data Engineer - Data, Analytics & AI (Bengaluru)
🏢 Travco Group
📍 Bengaluru