Temporary - Data Engineer

American Chemical Society•Boston, MA

1d•$45 - $48

About The Position

The American Cancer Society (ACS) is seeking a skilled Data Engineer to join our mission-driven team in the fight against cancer. As a key member of ACS’s growing enterprise data practice, the Data Engineer will play a central role in designing, building, and optimizing a modern data ecosystem leveraging Microsoft Azure, Snowflake, and Dbt. This position will focus on developing scalable, high-performance data pipelines and infrastructure to enable advanced analytics, machine learning, and research insights across the organization. Working closely with the Senior Director of Data and collaborating with analytics engineers and data scientists, the Data Engineer will help establish and enforce best practices in data architecture, automation, and governance. This is an opportunity to shape the foundation of ACS’s data capabilities and make a meaningful impact through data innovation.

Requirements

Bachelor's Degree in Computer Science, Engineering, Computational Biology, or equivalent experience
3+ years of relevant work experience.
3+ years of building a modern data pipeline, including the ETL, cloud-storage, reporting, and deployment
Advanced proficiency in cloud data engineering within Microsoft Azure, including services such as Azure Data Factory, Azure Databricks, and Cosmos DB; experience with Snowflake for data warehousing and administration.
Strong expertise in SQL and Python, including development of complex ETL/ELT workflows, automation scripts, and performance-optimized data transformations.
Hands-on experience with modern orchestration and ingestion platforms such as Prefect.io, Apache Airflow, FiveTran, Rivery.io, or OpenFlow, supporting automated and scalable data movement.
Proven experience implementing CI/CD practices for data engineering — including automated testing, code reviews, version control (e.g., GitHub/GitLab), and deployment pipelines.
Experience designing and managing large-scale, high-density data systems, including structured, semi-structured, and unstructured data such as genomics, imaging, and biospecimen datasets.
Familiarity with BI and visualization tools (e.g., Power BI, Tableau, Looker) and the ability to translate complex research or analytic requirements into optimized data models.
Strong understanding of healthcare and research data domains, including claims, electronic health records (EHR), survey, and clinical datasets; knowledge of data governance, compliance, and privacy standards (e.g., HIPAA).
Demonstrated collaboration skills working with data scientists, analytics engineers, and researchers to deliver high-quality, reliable, and well-documented data solutions.

Nice To Haves

Preferred Degree: Choose an item.
Certificate(s) or License(s):
Driver’s License Requirement(s) [Included only if driving is part of the job duties]:

Responsibilities

Design, develop, and orchestrate modern data pipelines and integrations (30%) — Architect and manage scalable data workflows using Azure Data Factory, Snowflake, dbt, and cloud orchestration tools such as Prefect.io or Airflow, ensuring high performance and reliability.
Implement and manage cloud-based data infrastructure (20%) — Administer and optimize data environments in Microsoft Azure, including Cosmos DB, Snowflake, and related services, performing configuration, monitoring, and cost optimization.
Develop and deploy advanced data engineering solutions (20%) — Utilize Python for complex data transformation, automation, and performance optimization within robust CI/CD pipelines with comprehensive unit testing and peer code reviews.
Integrate data from diverse sources (10%) — Leverage ingestion platforms such as FiveTran, Rivery.io, or OpenFlow to streamline and automate data collection from internal and external systems.
Collaborate with cross-functional teams (10%) — Partner with analytics engineers, data scientists, and business stakeholders to design and refine data models that power research, visualization, and machine learning initiatives.
Support data governance, security, and documentation (10%) — Implement and enforce best practices for data security, access control, and compliance, including Snowflake user and instance management.