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| Job Position | Company | Posted | Location | Salary | Tags |
|---|---|---|---|---|---|
Crypto.com | Singapore, Singapore | $88k - $101k | |||
Binance | Dubai, United Arab Emirates |
| |||
Phantom | San Francisco, CA, United States | $200k - $250k | |||
Trojan Trading | Spanish Town, British Virgin Islands | $150k - $350k | |||
| Learn job-ready web3 skills on your schedule with 1-on-1 support & get a job, or your money back. | | by Metana Bootcamp Info | |||
Trojan Trading | Spanish Town, British Virgin Islands | $150k - $350k | |||
Trojan Trading | Europe | $100k - $350k | |||
Trojan Trading | Europe | $100k - $350k | |||
JetSet Token | Las Vegas, NV, United States | $45k - $75k | |||
Robinhood | Toronto, Canada | $145k - $170k | |||
Binance | Bangkok, Thailand |
| |||
Kast | Remote | $94k - $104k | |||
Superduper | United Kingdom | $98k - $112k | |||
Tether | Medellin, Colombia | $115k - $120k | |||
Tether | Dublin, Ireland | $115k - $120k | |||
Tether | TI Lugano CH | $115k - $120k |
Crypto.com
$88k - $101k estimated
Analytics Engineer- Data Operations & Governance
Singapore, Singapore
Product Management & Product Design – Product Management /
Full-time /
Hybrid
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Responsibilities:
- Data Operations & Governance:Â Own the accuracy, reliability, and structure of product and user-event data through robust governance practices; Define and enforce standards for event tracking, data schemas, and documentation across teams; Conduct regular audits, validation checks, and coordinate instrumentation changes with engineering and product teams.
- Data Pipeline Development & Maintenance:Â Build and maintain scalable, observable data pipelines using tools like dbt, Airflow, or similar frameworks; Monitor pipeline health, implement alerting systems, and resolve data issues with root cause analysis; Optimize pipeline performance and ensure high availability of core datasets for analytics and reporting.
- Internal Tooling & Automation:Â Develop and maintain internal data tools, utilities, and dashboards using SQL, Python, and lightweight web technologies; Automate workflows to reduce manual reporting and improve operational efficiency for data stakeholders; Create reusable data models that support fast iteration and confident self-service analysis.
- Competitive Intelligence & Data Collection:Â Operate and enhance data scraping workflows to collect structured information on competitors, pricing, and market trends; Ensure scraping systems are stable, maintainable, and compliant with data privacy and ethical standards.
Requirements:
- Engineering Foundation: Strong SQL and working proficiency in Python or JavaScript for building and maintaining data infrastructure; Experience with modern data engineering tools (e.g., dbt, Airflow, Fivetran, Dagster); Familiarity with version control (Git), code modularization, and documentation practices.
- Data Quality & Governance Experience: Track record designing or maintaining data governance practices in product analytics environments (e.g., Segment, GA4, Mixpanel); Comfortable building QA checks, anomaly detection, and data validation processes; Familiarity with data governance education and data governance related stakeholder management
- Operational Mindset: Comfortable being on point for data issues, debugging pipeline failures, and ensuring continuity in reporting and dashboards; Ability to set up alerting/logging mechanisms to proactively detect and respond to data problems
- Collaboration & Communication: Strong written and verbal communication skills to align with product, engineering, and business teams; Able to translate business questions into engineering requirements and technical work into stakeholder-friendly language.
- Preferred Qualifications: Prior experience / knowledge on data science / machine learning; Prior experience on hands-on data engineering; Understanding of data operation & governance in analytics workflows; Experience supporting data for experimentation or A/B testing pipelines.
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