As a Senior BI Developer, you will be a key individual contributor building trusted data products for Agoda’s technology organization, including curated datasets, metrics, dashboards and visualizations, and scalable data transformations. You will work closely with engineers, engineering managers, team leads, and senior leadership to help the organization make better decisions with data. This role combines analytics, metrics definition, and stakeholder consulting with hands-on data engineering and development IN THIS ROLE, YOU’LL GET TO • Act as a partner and consultant to engineering managers and leaders: translate stakeholder and engineering questions into measurable metrics/information such as developer velocity, cost efficiency, and code quality, and keep those definitions consistent across reports. • Design, build, and maintain ETL/ELT transformations, including Spark/Python workflows and warehouse models, so data is accurate, timely, tested, and fit for reporting. As a Senior, review others’ pipeline and metric work, raise delivery standards, and unblock the team. • Analyze large datasets with SQL and Python to support engineering and operational decisions. • Design and maintain dashboards and visual reports so engineering managers and leaders can explore metrics (for example developer velocity, cost efficiency, and code quality) without a ticket for every chart. • Improve data reliability through validation, quality checks, observability, production troubleshooting, and query performance tuning. Own published metrics: explain filters and grain, flag numbers that should not be trusted, and recommend next steps. • Use AI tools (for example Cursor, Claude, or similar) to accelerate SQL development, testing, refactoring, analysis, pipeline work, and documentation, and reject unsafe or unverified output before it reaches production or stakeholders. WHAT YOU’LL NEED TO SUCCEED • 5+ years in business intelligence, analytics, and/or data engineering, with experience in both stakeholder consulting and hands-on pipeline or data-product work. • Advanced SQL (joins, window functions, and performance on large datasets). • Strong Python skills (or similar) for building data pipelines. • Experience with ETL/ELT and orchestration (for example Kubeflow or similar). • Strong analytical thinking: comfortable framing business questions, exploring data, and turning results into clear insights. • Experience building dashboards or visual reports for stakeholders. • Ability to switch context between stakeholder discussions and hands-on technical work — metrics definition/analysis one day, ETL or data modeling the next. • Practical AI-assisted development: generate, review, test, and own the result. You can explain what you trusted AI to draft and what you verified yourself. • Clear written and verbal English, and the ability to work independently with engineers and leaders in an agile environment. IT’S GREAT IF YOU HAVE • Experience with software-delivery practices such as Agile/Scrum and CI/CD (GitHub Actions, GitLab CI, or similar). • Interest in developer productivity or engineering analytics. • Experience with common data platforms / big data technology (e.g., BigQuery, Snowflake, Redshift, Hive, Spark, Vertica, StarRocks, or similar). • Hands-on experience with visualization or data-serving UIs such as Apache Superset, Tableau, or a lightweight web app. • Experience building APIs or internal data products beyond dashboards, not only ad-hoc analysis. • A degree in Computer Science, Engineering, Information Systems, or equivalent practical experience.

**Roles and Responsibilities** * Design and implement scalable, reliable, and efficient data pipelines for ingesting, processing, and storing large amounts of data from a variety of sources using cloud-based technologies, Python, and PySpark. * Build and maintain data lakes, data warehouses, and other data storage and processing systems on the cloud. * Write and maintain ETL/ELT jobs and data integration scripts to ensure smooth and accurate data flow. * Implement data security and compliance measures to protect data privacy and ensure regulatory compliance. * Collaborate with data scientists and analysts to understand their data needs and provide them with access to the required data. * Stay up-to-date on the latest developments in cloud-based data engineering, particularly in the context of Azure, AWS and GCP, and proactively bring new ideas and technologies to the team. * Monitor and optimize the performance of data pipelines and systems, identifying and resolving any issues or bottlenecks that may arise. **Qualifications** * Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field. * Minimum of 5 years of experience as a Data Engineer, with a strong focus on cloud-based data infrastructure. * Proficient programming skills in Python, Java, or a similar language, with an emphasis on Python. * Extensive experience with cloud-based data storage and processing technologies, particularly Azure, AWS and GCP. * Familiarity with ETL/ELT tools and frameworks such as Apache Beam, Apache Spark, or Apache Flink. * Knowledge of data modeling principles and experience working with SQL databases. * Strong problem-solving skills and the ability to troubleshoot and resolve issues efficiently. * Excellent communication and collaboration skills to work effectively with cross-functional teams.

You will serve as a key individual contributor within a scrum team dedicated to supporting the B2B entity. Your primary focus will be on designing, building, and maintaining high-quality data products, dashboards, and scalable data transformations. These assets are essential for enabling financial reporting, operational analytics, and data-driven decision-making across the organization. You will collaborate closely with Finance, Planning, Revenue Operations, Data Engineering, Product, and Analytics stakeholders to translate complex business requirements into trusted and efficient BI solutions. This role demands strong technical expertise, a high degree of ownership, and the ability to deliver reliable data assets that are accurate, performant, and aligned with specific business needs.

We are seeking a highly skilled Principal Customer Database Engineer to lead the design and implementation of robust data infrastructure solutions. This role requires deep expertise in database architecture and a proven track record of optimizing data performance at scale. You will be responsible for establishing best practices for data modeling, storage, and retrieval to ensure high availability and reliability. The ideal candidate will drive technical innovation and mentor junior engineers to build a resilient data ecosystem. In this position, you will collaborate closely with cross-functional teams to understand complex business requirements and translate them into scalable technical solutions. You will oversee the end-to-end lifecycle of database projects, from initial design and development to deployment and ongoing maintenance. Your work will directly impact the quality of data services and the overall efficiency of our systems. We value a proactive approach to problem-solving and a commitment to delivering high-quality software.

This role focuses on leading data analytics initiatives to drive strategic decision-making within the organization. You will oversee the development and implementation of business intelligence solutions that transform raw data into actionable insights. The position requires managing a team of analysts to ensure data accuracy and relevance for key business stakeholders. You will collaborate with cross-functional teams to identify trends and opportunities for operational improvement through data-driven strategies.

You will be responsible for designing, developing, and optimizing enterprise-scale data platforms on the Microsoft Azure Cloud. This role involves building scalable and secure ETL/ELT data pipelines to support Data Lake initiatives, analytics, and AI/ML projects. You will ensure high-quality, reliable, and cost-efficient data architecture while collaborating with cross-functional teams to deliver robust solutions and mentor junior engineers. Your day-to-day work includes designing cloud-based data architecture using Azure Data Factory, Databricks, and Microsoft Fabric. You will build ETL/ELT processes to integrate data from SAP, ERP systems, APIs, and Excel into the enterprise Data Lake. Additionally, you will develop and optimize SQL, Python, and PySpark scripts for large-scale data processing and monitor daily pipeline operations to troubleshoot complex technical issues.