Sr. Analytics Engineer, Financial & Card Issuance

ABCorp NA Inc.•Boston, MA

10h•Onsite

About The Position

ABCorp is seeking a highly skilled Senior Analytics Engineer to own the data and analytics strategy for our secure payment card solutions and enterprise SaaS products. This role will serve as a hybrid Data Analyst and Data Engineer, understanding the business problems to solve and building scalable data infrastructure to achieve business goals. The ideal candidate will possess strong analytical and technical skills, excellent communication abilities, and a proven track record of partnering with product and business teams to drive measurable impact through data. The ideal candidate will bring an intense focus on data quality and reliability, an ability to influence cross-functional stakeholders, strong product intuition paired with analytical rigor, and a passion for building scalable data models and self-service analytics capabilities. As a key partner to our Product and Engineering teams, you will help shape products that reach millions of people in their everyday lives across fintech, commercial, healthcare, and government industries worldwide. This is an in-person role with our team based in Boston, MA.

Requirements

Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, Economics, or a related field.
3-5+ years of experience in product analytics, data analysis, or analytics engineering roles, ideally supporting SaaS, payments, fintech, ecommerce, or enterprise software products.
Expert-level proficiency in SQL and experience with analytical data modeling, ideally using tools like dbt, SQLMesh, or similar frameworks.
Strong experience with data warehouses such as Snowflake, BigQuery, Redshift, or Databricks, and familiarity with ELT/ETL workflows.
Proficiency with BI and visualization tools such as Tableau, Looker, Mode, Hex, or similar platforms for building dashboards and reports.
Working knowledge of Python or R for data analysis, automation, and light data engineering tasks.
Demonstrated ability to translate ambiguous business questions into clear analytical frameworks and actionable recommendations.
Strong communication skills with the ability to present complex data insights to both technical and non-technical audiences.
Experience working cross-functionally with Product, Engineering, Sales, and Customer Success teams.
Comfort working with product analytics data including event tracking, user behavior, funnel analysis, cohort analysis, and retention metrics.
Ability to work onsite in Boston, MA.

Nice To Haves

Experience with experimentation, A/B testing, and statistical analysis is a plus.
Familiarity with payments, card issuance, authentication, identity, fintech, or secure manufacturing domains is a plus.
Self-starter mindset with strong ownership, attention to detail, and ability to work independently in a fast-paced, evolving environment.

Responsibilities

Partner closely with Product Management, Sales, and Customer Success teams to understand their data and reporting needs, translating business questions into structured analysis, metrics, and data-driven insights.
Build and maintain data warehouse models that serve as the source of truth for product usage, customer engagement, manufacturing efficiency, and business performance metrics.
Design, implement, and own key performance indicators (KPIs) and metrics frameworks that measure product success, user adoption, feature utilization, and business outcomes across our payment card manufacturing, enterprise SaaS, and digital issuance products.
Create dashboards, reports, and self-service analytics tools that enable stakeholders across Product, Sales, Customer Success, and Operations to access and act on data independently.
Model and integrate data from multiple sources including CRM systems, product usage events, manufacturing operations, billing systems, and customer feedback to power automation, enrichment, and operational workflows.
Collaborate with Product and Engineering teams on event instrumentation, schema design, and data collection best practices to ensure clean, reliable data capture.
Conduct deep-dive analyses on customer behavior, feature adoption, conversion funnels, retention patterns, and operational efficiency to identify opportunities and inform product roadmap prioritization.
Support experimentation and A/B testing initiatives by designing test frameworks, analyzing results, and communicating findings to stakeholders.
Own data quality, observability, and governance practices including documentation, testing, and monitoring to ensure trustworthy analytics.
Build forecasting models and contribute to strategic planning by providing data-driven projections on customer growth, revenue, and product performance.
Identify opportunities to automate reporting, improve data pipelines, and scale analytics capabilities as the business grows.
Serve as a trusted data partner and educator, helping teams across the organization develop stronger data literacy and make better decisions.