Staff Analytics Engineer

In 1989, Tim Berners-Lee envisioned a system to help CERN scientists share information more effectively. That vision became the World Wide Web – transforming how humanity connects and shares knowledge. Today, we're looking for someone who can architect the next evolution in how Mercury processes, understands, and acts on data.

We are looking for a Staff Analytics Engineer who can turn a universe of opportunities into impact. As the first Analytics Engineer to join our experienced, high-performing team of Data Engineers and Scientists, you will play a pivotal role during an exciting inflection point in our growth. Your innate curiosity and extensive experience will empower you to contribute across a diversity of initiatives both within and beyond the data domain, and you’ll do all this in collaboration with a team that will motivate and challenge you to deliver your absolute best. Come grow with us.

Responsibilities:

Contribute to the evolution of Mercury’s data quality, governance, and security strategies

• Contribute to the evolution of Data Team best practices and workflows to ensure that we are building a sustainable and scalable data function

• Drive adoption of new tools and methodologies to enhance data accessibility, discovery and documentation

Design and build scalable data pipelines and business-conformed data marts that enable better decision-making and data self-service

• Collaborate with cross-functional teams, including Engineering, Data Science, Product, Risk, InfoSec and Marketing to understand the needs of the business and how to serve them

• Mentor team members and foster a culture of continuous learning

• Support stakeholders to encourage data literacy in every department at Mercury

• Partner with Data Team leadership to align on departmental priorities

What we’re looking for:

• 7+ years of Analytics or Data Engineering experience

• Expertise with

  • A full modern data stack (Fivetran / Snowflake / dbt / Metabase / Hex or equivalents)

  • SQL, dbt, Python

• Experience with 

  • OLAP data modelling and architecture in support of self-service. Bonus if you have experience with OLTP data

  • Streaming / real-time data pipelines

  • Least privilege access patterns across data warehouse and visualization tooling. Bonus if you have zero trust access pattern experience

• Exposure to 

  • Serving data for ML and Generative AI use cases

  • The financial services industry (banking, insurance, accounting, or payments)

  • Data compliance standards (CCPA, GDPR, et al.). Bonus if you’ve implemented operational controls to comply with standards

Your values:

• Systems thinking - you’ll be representing the interests of the Data Team when influencing overall systems architecture and design

• Attention to detail - you’ll be contributing to the improvement of the Data Team’s practice and you’ll help ensure high quality standards are met

• Commitment to learning - you’ll be supporting and mentoring colleagues across Mercury in data

• techniques, tooling and best practice

• Thoughtful communication - you’ll be collaborating with people of varying technical competency across Mercury and helping to translate needs and intentions into action

The total rewards package at Mercury includes base salary, equity (stock options), and benefits. Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidate's experience, expertise, geographic location, and internal pay equity relative to peers.

Our target new hire base salary ranges for this role are the following:

• US employees (any location): $237,600-$279,000 

• Canadian employees (any location): CAD $216,200-$254,300  

Mercury is a financial technology company, not a bank. Banking services provided by Choice Financial Group, Column N.A., and Evolve Bank & Trust, Members FDIC.

We use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on January 22, 2024. Please see the independent bias audit report covering our use of Covey here.