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Senior Data Engineer

ABCorp NA Inc.

Job Description

Job Description

From our nation’s earliest days, ABCorp has been a trusted force in security and innovation. In 1795, the federally chartered Bank of the United States entrusted American Bank Note Company with the critical mission of producing counterfeit-resistant currency for the young Republic. This early history established our company, now known as ABCorp, as a pioneer in secure printing, with innovations that served not only American banks but also international clients, a legacy that shaped our evolution into a global leader in secure manufacturing. What began with protecting America’s financial foundation now drives cutting-edge solutions that safeguard organizations worldwide.

Today, ABCorp sits at the intersection where authentication, payments, and secure access embrace next-gen (including additive 3D) manufacturing to meet the demands of a digitally driven world. We have built 230 Years of Expertise – no one knows secure manufacturing and authentication better, and no one has done it longer. We maintain global reach and compliance with eight locations around the world, and we’ve been trusted by fintechs, financial institutions, healthcare companies, governments, and brands across 120+ countries. We deliver end-to-end innovation through high-security, state-of-the-art facilities that are incubators for advancements in payments, secure access, and additive manufacturing.

The Team

At ABCorp, we know that our legacy and decades of achievement are powered by an exceptional team that embodies a true startup mindset.

The Platform Engineering Team at ABCorp builds the data infrastructure layer that powers our entire analytics organization. We own the pipelines, integrations, and foundational data models that move business-critical data from our operational systems — ERP, manufacturing, finance, and CRM — into our modern data warehouse. Our team partners closely with Engineering, IT, Analytics, and Product teams to ensure that reliable, well-modeled data reaches every part of the organization, enabling data-driven decisions at scale.

Learn more about ABCorp's story, products and team at abcorp.com.

The Role

ABCorp is seeking a Senior Data Engineer to own the data infrastructure and pipeline layer that powers our business and operational analytics. Sitting at the foundation of our data organization, this role is responsible for building the reliable, scalable pipelines that move data from our manufacturing systems, ERP platforms, financial systems, and operational tools into our modern data warehouse — where it fuels analytics, reporting, and product decisions across the company. You will serve as the architect of our operational data layer, modernizing how we collect, move, and model business-critical data and building the foundation that the rest of the data organization depends on.

The ideal candidate brings deep data engineering expertise, a systems-oriented mindset, and a passion for building infrastructure that simply works — reliably, at scale, and with the rigor of a production software engineer. As a key partner to our Engineering, IT, and Analytics teams, you will help build the data backbone that supports products and decisions reaching millions of people worldwide across fintech, commercial, healthcare, and government industries — and mentor the engineers around you to raise the bar for how the organization works with data.

This is an in-person role with our team based in Boston, MA. Please note there is no Visa Sponsorship for this position.  

How You’ll Make a Difference:
  • Design, build, and own end-to-end data pipelines that move data from operational systems — including ERP (Infor Visual), CRM, billing, and manufacturing platforms — into Snowflake with reliability, observability, and testability built in from the start.
  • Lead the integration and modernization of data from legacy systems including Infor Visual (ERP) and SQL Server databases into our modern data warehouse, treating every migration as an opportunity to improve data quality and architecture.
  • Build and maintain dbt models that form the raw-to-staging foundational layer of our data warehouse — clean, tested, documented, and reliable sources that the Analytics Engineering team builds metrics and insights on top of.
  • Design and implement pipeline orchestration using Azure Data Factory (ADF), applying CI/CD practices, data contract testing, and infrastructure-as-code principles to ensure pipelines are maintainable and production-grade.
  • Identify and execute opportunities to modernize legacy data processes — replacing manual exports, fragile SQL scripts, and ad-hoc reporting workflows with properly engineered, maintainable pipelines.
  • Collaborate closely with the Analytics Engineering team to define the upstream data layer that their downstream models, metrics, and dashboards are built on — ensuring clean handoffs, clear data contracts, and shared understanding of data lineage.
  • Implement and own data quality monitoring, alerting, and observability practices that catch pipeline issues and data anomalies before they reach downstream consumers.
  • Manage and evolve the data platform infrastructure on Azure — including Azure Synapse Analytics, Azure Databricks, ADLS, compute resources, access controls, and cost optimization.

Who You Are
  • Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field.
  • 5+ years of experience in data engineering, with a track record of building production-grade ELT/ETL pipelines, data warehouse models, and data infrastructure in a modern cloud environment. 
  • Expert-level SQL proficiency including complex query optimization, performance tuning, and deep knowledge of data warehouse query patterns. 
  • Hands-on experience with dbt for data modeling, transformation, and testing — including lineage management, CI testing, documentation, and production-grade model ownership. 
  • Strong experience with cloud data warehouses, primarily Azure Synapse Analytics, and deep understanding of warehouse architecture, ELT patterns, and performance optimization. 
  • Strong Python proficiency for pipeline development, automation, and data engineering tasks — applied with software engineering discipline, not just scripting. 
  • Experience with Azure Data Factory (ADF) for pipeline orchestration, and familiarity with CI/CD and infrastructure-as-code practices applied to data pipelines. 
  • Experience with ERP systems and operational data — familiarity with platforms such as Infor Visual, SQL Server, SAP, or similar enterprise business systems is a strong plus. 
  • Deep experience with Azure data infrastructure — including Azure Synapse Analytics, Azure Databricks, Azure Data Lake Storage (ADLS), Azure Data Factory, Azure DevOps, and Azure Monitor. 
  • Proven ability to own complex, multi-month data engineering projects with minimal guidance — from architecture through to production deployment. 
  • Familiarity with event streaming systems, CDC pipelines, or large-scale schema migration projects is a plus. 
  • Self-starter mindset with strong ownership, engineering rigor, and comfort operating in a fast-paced environment where you help define how the data platform grows.
  • Ability to work onsite in Boston, MA.

 

Why Join ABCorp?
  • Unique opportunity to architect the data infrastructure layer for a global leader in secure manufacturing and payments — building systems that scale with a fast-growing, data-driven organization. 
  • Meaningful engineering challenges at the intersection of legacy ERP systems and modern data infrastructure — the chance to modernize how a 230-year-old company works with its operational data.
  • Close partnership with a growing Analytics Engineering team — your pipelines power their models, metrics, and the insights that shape our product roadmap.
  • Company with rich legacy of innovation and trust.
  • Incredible global team with collaborative work environment.
  • Competitive salary and benefits package.
  • Professional growth and development opportunities.

 

Vacancy posted a month ago
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