Data Engineer I

Founded in 2014, Circles is a global technology company reimagining the telco industry with its innovative SaaS platform, empowering telco operators worldwide to effortlessly launch innovative digital brands or refresh existing ones, accelerating their transformation into techcos.

Today, Circles partners with leading telco operators across multiple countries and continents, including KDDI Corporation, Etisalat Group (e&), AT&T, and Telkomsel, creating blueprints for future telco and digital experiences enjoyed by millions of consumers globally.

Besides its SaaS business, Circles operates three other distinct businesses

- Circles.Life : A wholly-owned digital lifestyle telco brand based in Singapore, Circles.Life is powered by Circles ’ SaaS platform and pioneering go-to-market strategies. It is the digital market leader in Singapore and has won numerous awards for marketing, customer service, and innovative product offerings beyond connectivity.

- Circles Aspire : A global provider of Communications Platform-as-a-Service (CPaaS) solutions. Its cloud-based Experience Cloud platform enables enterprises, service providers and developers to deliver and scale mobile, messaging, IoT, and connectivity services worldwide.

- Jetpac : Specializing in travel tech solutions, Jetpac provides seamless eSIM roaming for over 200 destinations and innovative travel lifestyle products, redefining connectivity for digital travelers. Jetpac was awarded Travel eSIM of the Year.

Circles is backed by renowned global investors, including Peak XV Partners (formerly Sequoia), Warburg Pincus, Founders Fund, and EDBI (the investment arm of the Singapore Economic Development Board), with a track record of backing industry challengers.

About this role

- We are looking for an experienced Data Engineer to design, develop, and support scalable data platforms and pipelines. The ideal candidate will have extensive experience with modern cloud-based data platforms, distributed data processing, Kubernetes, and data warehousing technologies. The role involves working closely with product teams, analytics, and platform engineers to deliver reliable and scalable data solutions across multiple markets.
- Reporting to a Senior Data Engineering, you will lead the architecture, creation, and support of robust data platforms and pipelines. Your work will focus on delivering cloud-native solutions that synchronize perfectly with our strategic data vision and overarching commercial goals.
- You will assume full end-to-end accountability for data initiatives, spanning from initial solutioning and testing to deployment and ongoing performance tuning. By providing dedicated production support and driving continuous enhancements, you ensure the ecosystem remains dependable and of the highest quality.

What you'll do

The Data Engineer I at Circles operates at the intersection of Data Engineering, Cloud Infrastructure, and Platform Engineering. You will be part of the team responsible for building, and maintaining scalable data platforms that power analytics, reporting, machine learning, and business operations across multiple markets. As a member of our team, your responsibilities include:

Circles is committed to a diverse and inclusive workplace. We are an equal opportunity employer and do not discriminate on the basis of race, national origin, gender, disability or age.

Responsibilities

Develop, and optimize scalable batch and streaming data pipelines using modern data engineering technologies.; Build and maintain cloud-native data platforms, including data lakes, data warehouses, and real-time data processing systems.; Take end-to-end ownership of data engineering initiatives, including solution design, development, testing, deployment, performance tuning, monitoring, and production support.; Collaborate with product, analytics, and engineering teams to understand business requirements and deliver reliable, high-quality data solutions.; Develop and optimize data models, ETL/ELT pipelines, and data integration frameworks to support business intelligence and operational reporting.; Experience deploying and managing data applications on Kubernetes, with hands-on experience in implementing CI/CD pipelines using GitLab CI/CD.; Monitor platform health, troubleshoot production issues, perform root cause analysis, and continuously improve system reliability and performance.; Align with the engineering best practices, and contribute to technical documentation, and knowledge sharing.; Head of Data Engineering; Data Platform & Engineering Teams; Product Managers; Analytics & Business Intelligence Teams; DevOps & Infrastructure Teams; External vendors and technology partners

Requirements

1+ years of experience in Data Engineering, or Big Data; Strong experience designing and building scalable ETL/ELT pipelines using Python, Spark/PySpark, and SQL .; Hands-on experience with modern data lakehouse technologies such as Apache Iceberg, Hive, Trino, Big query, Red shift, ClickHouse and Snowflake . (any one); Experience working with cloud object storage solutions such as Amazon S3 or S3-compatible object storage platforms.; Strong analytical and problem-solving skills with the ability to work independently in a fast-paced environment.; Excellent communication and stakeholder management skills, with the ability to collaborate effectively across cross-functional teams.

Nice to have

Experience building and supporting real-time data pipelines using Apache Kafka and distributed data processing frameworks.; Strong understanding of database technologies, including, any one RDBMS like Mysql, Oracle and MongoDB (optional), with expertise in SQL performance tuning and data optimization.; Experience developing data ingestion frameworks and integrating data from relational and NoSQL (optional) databases using SQLAlchemy, PyMongo, and other database connectivity frameworks.; Good to have experience deploying and managing applications on Kubernetes , with working knowledge of Docker and GitLab CI/CD pipelines.; LLM based application using LangGraph, MLOps; Experience monitoring, troubleshooting, and optimizing production data platforms, including root cause analysis and performance optimization.; Good understanding of distributed systems, data architecture, data governance, and security best practices.; Experience in the telecommunications domain and supporting multi-market data platforms is an advantage.; Familiarity with Agile development methodologies and tools such as JIRA .; Data Platform development, with a strong track record of delivering enterprise-scale data solutions.