Sr. Data Platform Engineer

Sr. Data Platform Engineer

Requirements

• Minimum 5 years experience using Python for data automation/ETL/ELT automation in a production capacity (e.g. Airflow, Git, Medallion Architectures)
• Experience working with and evolving / architecting Snowflake (or Databricks), DBT models in a production environment.
• Experience leading design/approaches in both transactional (OLTP) and analytical (OLAP) workloads.
• Strong working knowledge of Pandas/Polars/Dask, SQL.
• Comfort working with Linux, Bash in a professional environment.
• Experience using data replication technology in a data-warehousing context (e.g. Azure Data Factory, Qlik Replicate, etc).
• Experience working with and delivering data visualization and reporting using enterprise tooling (e.g. Sigma, Tableau, Power-BI).
• Passionate and knowledgeable about data products, platforms, and the evolving data landscape.
• Excellent quantitative, mathematical, and problem-solving skills.
• Ability to work with a fair degree of autonomy and demonstrate tremendous initiative and sense of personal accountability.
• Experience previously leading and delivering successful cross-functional data initiatives (business users, BI analysts, product managers).
• Intellectually curious out-of-the-box thinker who is passionate about brainstorming innovative ways to use data to solve business problems.
• At least 2 years experience in investment management, market data, financial services, or fintech.
• Strong at technical goal setting for a project with actionable success metrics. Good knowledge and experience on measuring a service from a user experience angle.
• Excellent communication and negotiation skills, capable of building enthusiastic support for new ideas and converting resistance to endorsement with robust collaboration with various stakeholders, leaders and agile team(s) across the organization.
• High level of attention to detail.

Responsibilities

• Coach the data team to deliver data and strategic approaches that help optimize BBR’s data insights and accessibility for both Front-Office and Middle-Office needs.
• Lead the efforts for modernizing data development techniques using modular, composable and (where possible) open-source technologies.
• Guide the establishment of high-performance, scalable, and reliable analytics platform using Cloud technologies to directly impact our analytics capabilities.
• Support analytics engineering, data engineering, and technology in furthering insights in funds, operations, and client intelligence.
• Implement, monitor, and govern enterprise data privacy policies and complying with data protection regulations.
• Establish data standards for analytical data over business terms, business definitions, enterprise code sets, data elements and business rules.
• Enable data usability, availability, and efficiency to create product strategies to address market needs and translate into a product roadmap.
• Aide in the delivery and patterns required to integrate data from various 3rd parties for research and mission critical applications, encompassing data monitoring and repeatability principles.

Preferred Qualifications

No preferred qualifications provided.