Data Engineer II

Blockchain technology is powering a growing wave of innovation. Businesses and governments around the world are using blockchains to make banking more efficient, connect with their customers, and investigate criminal cases. As adoption of blockchain technology grows, more and more organizations seek access to all this ecosystem has to offer. That’s where Chainalysis comes in. We provide complete knowledge of what’s happening on blockchains through our data, services, and solutions. With Chainalysis, organizations can navigate blockchains safely and with confidence.

The Data Engineering and Architecture (DEA) team is responsible for unlocking the value in Chainalysis’ corporate data. We work with internal stakeholders in HR, Finance, Sales and Marketing as well as partners in Business Technology and Core Engineering to ship data solutions that are trusted, reliable, mature and transformative. Our goal is to accelerate Chainalysis’ growth and empower our employees to do their best work. 

Priorities in your first year include:

• You've increased test coverage of our existing dbt models
• You’ve discovered and root-caused data quality issues in existing models
• You’ve worked with system-of-record owners and stakeholders to remedy upstream data quality issues
• You’ve contributed to bringing legacy dbt models into alignment with current best practices and structure
• You're working through a backlog of fixes and enhancements

Responsibilities:

• Improving the data quality, monitoring, and remediation of models in our existing data marts.
• Adding features/enhancements to these existing models that are currently in the backlog. 
• Partnering with colleagues in DEA as we spin up and maintain data pipelines that support critical data-driven decisions across the company.

Qualifications:

• You have experience writing robust SQL queries; ideally using Snowflake SQL syntax.
• You’ve worked as data analyst or data engineer
• You have an in-depth understanding of the capabilities and constraints of cloud-based data warehouses
• You have performing root cause analysis on data integration and automation errors while identifying opportunities to improve instrumentation and observability
• You possess a keen eye for catching edge-cases; not only where occurrences currently exist, but also theoretical ones that could exist given the known guarantees of the data structures
• You have worked with data from systems of record such as Salesforce, Workday, Jira, etc.
• You have the basic CLI skills necessary to execute our DBT project (explicit DBT experience is a plus but not required)
• You have hands-on experience with Github and source control
• You have experience in an Agile-like environment that includes user stories, sprints, grooming and retrospectives

Technologies we use (experience not required):

• Fivetran
• Github
• DBT
• Airflow
• Python
• Snowflake
• Redshift
• AWS (S3)
• Workato
• Jira
• GSuite

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