Data Engineer

About Bliink

Bliink is a Bali-based company that helps small medium businesses streamline their corporate travel management by automating processes and negotiating special corporate rates, saving them valuable time, money, and resources. The company was founded by a seasoned travel innovator with extensive experience in the internet and travel sectors, having worked with prominent companies such as Alibaba Group, Ensogo Group, and MG Group.

Our Purpose
- We simplify travel, saving time and money, so travellers can focus on what truly matters.

The Opportunity

To be part of the team that will redefine travel with AI that makes every trip smarter, faster, and more cost-effective.

Why Join Us?

• Work on cutting-edge tech with a talented, passionate team
• Flexible work environment
• Learn best practices from the team and founder's previous experience in Alibaba Group / Lazada and others

Our Beliefs:

We believe travel should be simpler, smarter and faster (no brainer).

• Technology Should Simplify, Not Complicate
• We believe that innovation should make things easier, not harder.
• Smarter Travel Drives Better Business
• We believe that intelligent travel solutions lead to greater efficiency and productivity.
• Every Journey Should Empower People
• We believe business travel should support people in doing their best work, not distract from it.

Job Description

Our company is looking for a self-driven and adaptable Data Engineer who will join our expanding workforce. Your role as a Data Engineer specializing in AI/ML will involve fundamental work in creating and preserving data infrastructure to enable us to produce and implement advanced AI/ML solutions. Your role involves creating data pipelines while guaranteeing data quality and access and you will team up with our AI/ML team to fulfill their research and development tasks.

Key Responsibilities:

• Oversee the end-to-end AI model lifecycle, including data collection, preprocessing, model training, evaluation, and deployment.
• Design, develop, and maintain scalable and reliable data pipelines for data ingestion, processing, and storage.
• Execute comprehensive data processing workflows to prepare data for AI/ML models, including:
• Data cleaning (handling missing values, outliers, inconsistencies).
• Data chunking and splitting for model training and evaluation.
• Data embedding and feature engineering.
• Data transformation and normalization.
• Build and optimize data warehouses and data lakes for efficient data retrieval and analysis.
• Collaborate with AI/ML engineers to support the development and deployment of machine learning models.
• Implement data quality checks and monitoring to ensure data accuracy and consistency.
• Develop and maintain data documentation and metadata.
• Troubleshoot and resolve data-related issues.
• Stay updated with the latest advancements in data engineering, AI and machine learning, incorporating best practices into projects.
• Ensure compliance with data privacy and security regulations.
• Implement and manage data collection from user activity tracking tools such as Google Analytics or Firebase Analytics.

Qualifications:

• Bachelor's degree in Computer Science, Data Science, Engineering, or a related field. Master's degree is a plus.
• Proficient in Python. Experience with other languages such as SQL, Java, or Scala is a plus.
• Strong understanding of data processing frameworks (e.g., Apache Spark, Apache Beam, Dask), machine learning libraries (e.g., TensorFlow, PyTorch), and data visualization tools (e.g., Matplotlib, Seaborn).
• Hands-on experience with cloud data analytics and warehousing platforms, such as Google Cloud Platform (BigQuery, Dataflow, Cloud Storage, BQML), Amazon Web Services (Redshift, Glue, S3), or Microsoft Azure (Synapse Analytics, Data Factory, Azure Storage). BigQuery experience is highly valued.
• Experience designing and implementing data warehouses and data lakes.
• Proven experience building and maintaining complex data pipelines.
• Strong understanding of data privacy and security regulations, such as GDPR, CCPA, and HIPAA.
• Experience with collecting and processing data from user activity tracking tools like Google Analytics or Firebase Analytics.
• Experience with MLOps concepts and tools.
• Experience with real time data streaming.
• Experience with Git or other version control systems.
• Excellent communication and collaboration skills.
• Strong analytical and problem-solving abilities.

Working Experience

• Minimum of 2-3 years of professional experience in data engineering.
• Experience working in a startup environment is a plus.
• Experience working with large datasets, and optimizing queries for performance.

What We Offer:

• Competitive salary and equity options.
• Flexible working hours and remote work options.
• Opportunity to work on cutting-edge AI and data technologies in the travel industry.
• Collaborative and inclusive work environment.
• Professional development opportunities and access to industry conferences.
• Travel perks and discounts (because we love travel too).