Analytics Engineer

We are looking for an Analytics Engineer at Flip. You will be our “agent of change” helping us not only build best practices around data pipelines but also support experimentation and implementation of agentic AI to enhance business intelligence, analytics, and potentially machine learning applications. In this role, you are expected to stay updated with the ever-evolving AI and data landscape, and proactively identify corresponding use cases.

About Flip

Rafi, Luqman, and Anjar, who were college friends in Universitas Indonesia, started Flip as a project in 2015 to transfer payments to each other at a fraction of what banks would charge them. They are pioneers in the Indonesian market, with their technology now helping millions of Indonesians, both individuals and businesses, carry out bank-to-bank money transfers through a reliable and seamless app.

After nine years of operations, Flip has helped Indonesians transfer money worth several trillions of rupiah and has received double-digit funding from respectable investors such as Sequoia India, Insight Partner, and Insignia. Flip’s ultimate mission is to give Indonesians access to one of the most progressive and fairest financial services in the world.

At Flip, we always strive to provide the fairest place for you to work, learn, and grow with talented and fun people in various opportunities to advance your career and get fair rewards. We believe that we have to treat employees, customers, and all stakeholders fairly and respectfully. Fair treatment for employees means we establish clear goals, facilitate our employees to achieve them, and value their contribution to the company with equitable benefits.

Key Responsibilities:

• Build and maintain scalable, reliable data models/pipelines using tools like dbt, SQL, Python.
• Design and implement scalable, reliable, and high-performance data architecture following best practices and strategies for data processing, storage, and retrieval.
• Design and optimize data workflows that support analytical use cases, experimentation, and real-time reporting
• Work closely with analysts, product managers, and engineers to deliver insights and enable data-driven decision making
• Build and operationalize LLM-based or agentic AI systems, including fine-tuning pipelines, embedding usage, and feedback loops
• Contribute to governance, documentation, and observability of data assets and AI-enabled processes
• Ensure data quality, lineage, and performance across internal and AI-driven services

Requirements:

• 3+ years of experience as an Analytics Engineer, AI Engineer, or Data Engineer role
• Proficiency in SQL, Python, and data transformation tools like dbt
• Strong understanding of data warehousing concepts, preferably with platforms like BigQuery, Snowflake, or Redshift
• Strong knowledge of GCP stacks (Bigquery, Datastream, Dataflow, Pub/Sub, etc)
• Experience integrating or working with LLMs (e.g., OpenAI, Claude, Llama) for internal tools, workflows, or end-user applications is a must
• Familiarity with embedding models, vector databases (e.g., Pinecone, FAISS)
• Demonstrated ability to build clean, modular, and reusable code and data models.
• Excellent communication skills to collaborate across business and technical stakeholders.

Nice to Have:

• Knowledge of open source stacks (Debezium, Kafka, duckDB)
• Experience with data observability tools 
• Background in analytics or experimentation, including A/B testing frameworks
• Experience with real-time or event-driven data processing (e.g., Kafka, Pub/Sub)
• Prior work in fintech, marketplaces, or AI-native companies