Coingecko8mo ago

Senior Software Engineer, Data (L3)

MalaysiaRemoteFull-timesenior

Data EngineeringSoftware EngineerSoftware Engineering

0 views0 saves0 applied

Apply Now

Quick Summary

Requirements Summary

Provide feedback on the performance of junior staff and participate in people development initiatives. Support any ad hoc tasks as required by the company.

Technical Tools

Data EngineeringSoftware EngineerSoftware Engineering

CoinGecko is a global leader in tracking cryptocurrency data. Operating since 2014, CoinGecko has built the world's largest cryptocurrency data platform, tracking over 10,000 tokens across more than 400 exchanges, serving over 300 million page views in more than 100 countries, and handling more than 45 billion API calls every month. We are proud to have played a major part in mainstream awareness, adoption, and education of cryptocurrency globally.

We at CoinGecko believe that cryptocurrency and blockchain will define the future of finance, bringing greater financial and economic freedom around the world. In anticipation of that future, CoinGecko is building the foundation to scale cryptocurrency market data to serve billions.

We practice transparent salaries and a level structure at CoinGecko:

• The salary for this position is RM16,899 - RM18,589.

• Learn more about our level structure at CoinGecko's Career Progression.

Note: This is a remote-first role based in Malaysia, and only candidates based in Malaysia will be considered.

Data Pipeline Development: Design, build, and maintain scalable data pipelines that process high-volume, multi-source data feeds. Implement robust data models using star schema and dimensional modeling techniques to ensure data consistency, accuracy, and accessibility across the organization.

Data Architecture & Infrastructure: Own end-to-end data infrastructure including pipeline orchestration, data warehousing, and OLAP systems. Manage cloud-based deployments and ensure optimal performance, cost efficiency, and reliability of data processing systems.

Data Quality Management: Establish and maintain comprehensive data quality frameworks including automated validation, monitoring, and remediation processes. Define and track data quality KPIs and implement systematic approaches to data governance and lineage. Continuously monitor and optimize data pipeline performance, reducing latency, costs, and complexity while maintaining data integrity and reliability.

Technical Leadership: Provide code reviews, technical direction, and mentorship to junior team members. Contribute to architectural decisions and drive adoption of data engineering best practices across the organization.

Documentation & Knowledge Sharing: Create and maintain comprehensive technical documentation, contribute to team knowledge bases, and participate in cross-functional learning initiatives.

Incident Response: Lead troubleshooting efforts for data-related issues, participate in post-mortems, and implement preventive measures to improve system reliability.

Sharpen the Saw: Stay up-to-date with emerging trends and technologies to propose improvements and proof-of-concepts in technical roadmaps. Be a subject matter expert in multiple parts of the technological stack. Take initiatives and support upskilling activities within the team.

Team Player: Partner with data analysts, product managers, and business stakeholders to translate requirements into scalable technical solutions. Provide technical guidance on data methodology and contribute to strategic data product initiatives.

Coaching: Provide feedback on the performance of junior staff and participate in people development initiatives.

Support any ad hoc tasks as required by the company.

Proven Track Record: 5-8 years of data engineering experience with proven track record in building production-scale ETL/ELT pipelines, data warehousing, and analytics infrastructure to produce B2B and B2C data products.

Education: Bachelor's degree in Computer Science, Data Engineering, Software Engineering, or related technical field, or equivalent professional experience.

Technical Proficiency: Professional experience with cloud data warehouses (ClickHouse, BigQuery, Snowflake, Redshift), Python and common libraries (pandas, dask, pyarrow, pytest), workflow orchestration tools (Dagster, Airflow, or similar), stream processing technologies (Kafka, Flink, or similar). Knowledge of data modeling, dimensional modeling, and schema design principles.

Infrastructure & DevOps: Experience managing cloud infrastructure, containerization, and CI/CD pipelines for data applications. Comfortable with infrastructure as code and deployment automation.

People Skills: Excellent communicator who is able to build positive working relationships within the team and externally. Contributes thought leadership outside of day-to-day work.

Leadership: Self-motivated and able to work independently with minimal supervision. Has a strong sense of shared leadership and values over all team members. Is curious & creative on finding ways to improve existing projects & workflows.

Scope of Work: Works effectively in open-ended projects, where some, but not all, key results are clearly defined. Fully capable of taking substantial features from concept to shipping as a sole contributor.

Problem Solving: Demonstrated ability to provide multiple solutions to complex problems, using sound judgment and arguments to present a well-structured, informed narrative.

Nice to have:

// Experience working in an early-to-growth stage startup.

// Experience building applications in different tech stacks.

// Keen interest in decentralized technologies and its applications including cryptocurrencies.