Senior Engineering Manager, Data Analytics – Data & AI

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🕒 January 23

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Logo of Kraken Digital Asset Exchange

Kraken Digital Asset Exchange

1001 - 5000 employees

Founded 2011

₿ Crypto

💸 Finance

💳 Fintech

Crypto • Finance • Fintech

Kraken Digital Asset Exchange is a cryptocurrency platform that facilitates the buying and selling of over 200 cryptocurrencies, including Bitcoin, Ethereum, and many others. Founded in 2011, Kraken provides a comprehensive suite of features for both beginner and advanced traders, such as advanced trading interfaces and margin trading. The platform emphasizes industry-leading security, deep liquidity, and 24/7 customer support, making it a trusted choice for users worldwide. Kraken caters to individual investors as well as institutional clients, offering services like OTC trading and custody. The company is committed to transparency with its proof of reserves and mission-driven values. Kraken operates globally, supporting clients in over 190 countries, with a quarterly trading volume exceeding $207 billion. However, users are advised of the high risk of crypto investments and the lack of regulation in some jurisdictions.

📋 Description

• Drive decision making in building cutting-edge products. • Transform large datasets from complex systems, generate actionable insights, and share the results with stakeholders at all levels of the company. • Partner and lead projects with product management, engineering, client engagement, finance, and other enterprise level teams. • Build out analytics and management report dashboards by collaborating closely with directors and cross functional teams to infuse analytics insights into major business priorities and enable data driven decisions. • Partner closely with data engineering and enterprise systems team to define, plan, implement, and support the data infrastructure. • Lead the definition of data requirements and controls to enable the integrity of the company’s analytics and management reporting. • Drive projects and initiatives for assessment of current data and process infrastructure to support team objects. • Support data analysis and reporting requirements, building and maintaining knowledge repository and technical documentation libraries for data lake and reporting. • Run standup, workgroup meetings, identifying action items and addressing blockers to keep projects on track.

🎯 Requirements

• Master’s degree or the equivalent in Computer Science, Management Information Systems, or a related field plus 8 years of experience in data analytics or related experience. • Experience with Data pipelines, ETL/ELT, data warehousing, and orchestration tools; BI tools (Tableau, Looker or similar); • Data platforms such as Snowflake, Big Query, Redshift; and observability and experiment platforms; • Statistics experimentation (A/B testing), modeling techniques and casual inference; • Languages such as Python, SQL, Scala, or Java for data systems; • Hiring a technical team, including providing feedback and mentoring for career growth; • Translating business problems into technical plans; • Driving strategy for data products and platforms, such as self-serve analytics; • Balancing long-term tech investments with short-term business needs; • Agile or hybrid methods tailored to analytics projects; • Working with product and business leaders to define KPIs, dashboards, and success metrics for product performance; • Aligning data strategy with company and product goals; • Driving data quality, engineering best practices, and scalable systems.

🏖️ Benefits

• Offers Equity • Offers Bonus

Apply Now

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