Data Engineer

The Paper Store•Acton, MA

11d•$80,000 - $98,000•Hybrid

About The Position

TPS Group Holdings, a family of brands including The Paper Store, Uncharted, and Gifts & More, is all about transforming daily routines into joyful escapes that inspire and surprise. Our mission is to connect with every customer through carefully chosen products, immersive shopping experiences, and service that goes the extra mile — creating a space that sparks joy with every visit. The Role: We are seeking an experienced Data Engineer to own and optimize end-to-end data pipeline operations across our Snowflake data warehouse environment. This is a highly technical, hands-on role focused on building, maintaining, and scaling production-grade ETL pipelines. Direct experience with Matillion, SSIS, and Snowflake is required. This role is best suited for someone who has built and supported enterprise data pipelines using these platforms and is comfortable working in a production environment. The Data Engineer will be responsible for ensuring operational visibility, data quality, and the overall reliability of our data ecosystem. This is not a general analytics or BI role; it requires strong ETL engineering expertise and the ability to support a growing, evolving data environment.

Requirements

2+ years of relevant data engineering experience.
Hands-on experience with Matillion is required.
Hands-on experience with Snowflake is required.
Experience with SSIS or similar ETL tools is required.
Strong SQL skills, including writing queries, joins, stored procedures, and data transformations.
Experience building, maintaining, and supporting ETL pipelines in a production environment.
Proficiency in data modeling and database management.
Experience with data warehousing and cloud-based data platforms.
Strong programming skills, such as Python, Java, or SQL.
Understanding of data quality, data validation, error handling, and data governance practices.
Ability to troubleshoot pipeline failures, performance issues, and data discrepancies.
Strong documentation skills and attention to detail.
A team-player mindset, including the willingness to pivot as business needs change and assist others to meet deadlines.
Ability to work 3+ days per week at the Corporate Office in Acton, MA.
5+ years of hands-on Data Engineering experience
Strong SQL expertise (complex queries, optimization, performance tuning)
Proven experience building ETL pipelines using Matillion
Proven experience developing ETL processes in SSIS
Direct experience working with Snowflake data warehouse
Strong understanding of data modeling and data warehousing architecture
Ability to work 3+ days/week at the Corporate Office in Acton, MA.

Responsibilities

Design, develop, and maintain production-grade ETL pipelines using Matillion and SSIS.
Build, optimize, and maintain data models within Snowflake.
Develop and maintain data pipelines that support efficient data extraction, transformation, and loading processes.
Integrate new data sources into enterprise data pipelines.
Monitor data infrastructure for performance, reliability, and operational visibility.
Ensure data quality and integrity through validation, cleansing, error handling, and data controls.
Improve the performance, scalability, and robustness of existing data infrastructure.
Design and optimize data storage solutions, including data warehouses and data lake environments.
Partner with data analysts, data architects, software engineers, and business partners to understand data requirements and deliver reliable data sets.
Support business intelligence needs by ensuring data is accurate, accessible, and structured for reporting and decision-making.
Implement data security measures and access controls to protect sensitive information.
Automate and improve data processes and workflows for scalability and efficiency.
Document data pipelines, processes, standards, and best practices for knowledge sharing.
Partner with cross-functional teams to support data governance, compliance, and data-driven decision-making.
Stay current on industry trends and emerging technologies in data engineering.
Provide technical guidance and support to junior team members, if applicable.
Continuously optimize data architecture to support the company’s evolving data needs.