Über
Valuable Insights : Equip stakeholders by transforming business requirements into scalable data models, dashboards, and tools.
Collaborative Solutions : Work alongside engineering, data science, product, and business teams to align priorities and data solutions.
Efficient Data Products : Create frameworks, tools, and workflows that enhance efficiency for data users while ensuring high standards of data quality.
Results-Oriented Delivery : Utilize modern development and analytics tools to bring value quickly while maintaining long-term usability.
Your Responsibilities: The Analytics Engineer role is a hybrid of Data Engineer, Data Scientist, and Business Analyst, requiring a deep understanding of end-to-end data flows and the engineering skills to extract maximum value from that data by building tables and delivering insights. Subject Matter Expertise:
Quickly develop expertise in specific business areas and data domains. Comprehend the data flows from their creation to delivery.
Examples:
Collaborate with Engineering and Product partners to create initial data pipelines and insights for new business lines.
Engage with engineering teams to resolve data discrepancies impacting downstream users.
Take proactive steps to address issues across the data stack.
Generate Business Value:
Interface with stakeholders to yield the most commercial value from data.
Examples:
Develop a new data model that empowers downstream Data Science teams to realize business value through experimentation and analyses.
Integrate engineering details with statistical and data expertise to propose improvements for algorithms.
Collaborate with Product Managers to integrate new cross-product data into a comprehensive framework optimizing key business metrics.
Outcome-Driven Focus:
Employ a variety of frameworks to identify and implement the best tools for delivering value.
Examples:
Create new abstractions (e.g., UDFs, Python packages, dashboards) for scalable data workflows and infrastructure.
Develop an internal framework for building data applications, allowing Data Science teams to add value swiftly.
Utilize established tools effectively (e.g., Google Sheets, SQL) for rapid delivery of impactful results.
What We Look For: In addition to innovative thinking, attention to detail, a strong sense of urgency, and high accountability, we seek candidates with the following skills: Data Modeling Expertise:
Deep understanding of best practices for designing modular and reusable data models (e.g., star and snowflake schemas).
Prompt Design and Engineering:
Proficiency in prompt engineering and design for LLMs (e.g., GPT), including the creation and optimization of prompts.
Advanced SQL:
Strong knowledge of advanced SQL techniques for data transformation and optimization.
Intermediate to Advanced Python:
Skilled in scripting and automation, with experience in Object-Oriented Programming.
Communication and Collaboration:
Ability to translate technical concepts into business value and manage projects across various teams.
Data Pipeline Development:
Proven experience in building and optimizing ETL/ELT pipelines using modern tools like dbt or Airflow.
Data Visualization:
Competence in creating polished dashboards utilizing tools such as Looker, Tableau, or Python visualization libraries.
Development Tools:
Familiarity with version control systems (GitHub), CI/CD, and modern development practices.
Data Architecture:
Knowledge of contemporary data lakes and warehouse architectures (e.g., Snowflake, Databricks).
Business Acumen:
Ability to identify and address business challenges through analytics engineering.
Data Savvy:
Understanding of statistics and probability.
Bonus Skills:
Experience with cloud platforms (e.g., AWS, GCP).
Familiarity with Docker or Kubernetes.
Please note: Submitting for this position does not guarantee consideration for it. Leveling and team matching will be assessed during the interview process. ID: G2754 *Pay Transparency Notice: * Depending on your work location, the target annual *base *salary for this position ranges from $180,000 to $212,000 USD, in addition to potential bonuses and benefits including medical, dental, vision, and 401(k). We encourage you to evaluate your skills and interests in relation to Coinbase's roles before applying, as each candidate may submit a maximum of four applications in a 30-day period. Equal Opportunity Commitment:
Coinbase proudly stands as an Equal Opportunity Employer. All qualified applicants will be evaluated without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, sex, gender expression or identity, sexual orientation, or any other protected basis. We also consider qualified applicants with criminal histories in accordance with applicable laws. For US applicants, you can view the Employee Rights and Know Your Rights notices. Additionally, Coinbase participates in the E-Verify program as required. Coinbase is dedicated to providing reasonable accommodations for individuals with disabilities. If you require accommodation during the employment process, please contact us to communicate your request and contact information. Global Data Privacy Notice:
Depending on your location, various regulations such as GDPR and CCPA govern the handling of data from job candidates. Available notices detail data processing practices consistent with applicable laws. AI Screening Disclosure:
For certain positions, Coinbase is testing an AI tool for initial screening interviews. A human recruiter will review your responses for alignment with our job requirements. Please be aware that our AI tools do not impact employment decisions.
Sprachkenntnisse
- English
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