Analytics Engineering Manager, iCapital

• Bachelor’s degree or higher in Computer Science, Economics, Mathematics, Statistics or a related technical field
• 5 to 9 years of experience in an data-related role
• Excellent writing, communication and presentation skills
• Excellent knowledge of SQL (dbt experienced preferred)
• Excellent knowledge of Python, Microsoft Excel and intermediate statistics
• Excellent knowledge of data modeling, relational databases, normalization, OLAP stores
• Good knowledge of data science techniques and machine learning models
• Good knowledge of a business intelligence tool (e.g. Tableau, Looker, PowerBI)
• Good knowledge of learning data governance principles, data stewardship, traceability, lineage

Desirable

• We’re looking for an Analytics Engineering Manager, Vice President to measurably drive growth for our business teams at iCapital using data
• This role would involve managing a team of analytics engineers, working with business stakeholders to understand project requirements and define key outcomes, and finally developing and executing on implementation plans
• This role involves both management and individual contribution
• You will be expected to work with various department leads (e.g. sales, marketing, finance, product, operations), understand their pain points and business processes, and ultimately develop data-driven solutions to solve their needs
• These solutions span data ingestion, centralization, governance, business intelligence and machine learning
• While you will have a team to assist you, you are also expected to be heavily involved in all technical details of the project
• While not all of our work directly involves software engineering, almost all of it is heavily informed by software engineering principles
• The actual outputs of our work can be: clean and well-governed data models, management dashboards, exploratory/statistical data analyses (with attendant recommendations), documentation, machine learning models, or data apps
• You will sit in the Analytics group of the broader Data Office team and work closely with our Data Engineering and Data Science teams
• On the technical side, you will interface with our entire data stack of Airbyte, Snowflake, dbt, Prefect, Python, Tableau and SageMaker (among others)
• On the business side, you will work with our sales, marketing, operations, product and finance teams to drive top-line growth metrics (e.g. sales, usage, conversion)
• This is a technical role where you will be writing code
• Ideal candidates will be able to understand complex business problems, interface with senior stakeholders, develop execution plans, implement all aspects of the project technically, and finally present on their work
• Manage of team of analytics engineers in project scoping, unblocking technical challenges and ensuring timely delivery of work
• Drive projects to completion by gathering business requirements, implementing technical solutions, following software engineering best practices, and finally presenting on results
• Write Python and SQL (in dbt) to extract, transform, validate, and aggregate data
• Create Tableau dashboards for various business teams, charting key metrics and performing exploratory data analysis
• Develop statistical models and construct data-driven experiments
• Convert data insights into concrete, action-oriented and phased execution plans that measurably grow various business metrics over time
• Work closely with our engineering, product and business teams to form a thorough understanding of our industry and evolving data model