Data Engineer

The Data Engineer will provide technical leadership responsibility for building and managing enterprise-wide data transformation and orchestration processes and data pipelines. This work will require expertise in several layers of our enterprise data infrastructure, including our diverse source systems, our medallion-modeled data lakehouse, data activation platforms, and the orchestration and transformation of data as it flows throughout the entire data estate. Responsibilities include but are not limited to:

• Provides technical leadership in data pipeline design and development organization-wide, ensuring data flows are orchestrated in alignment with business needs and system architectures. Emphasis will be on ingestion, unifying transformations, and deliveries to activation platforms via the data lakehouse.
• Ensures that designs and techniques are compliant with system architectures as well as data management and governance standards and policies in place within the organization.
• Uses agile software development processes, in collaboration and alignment with the development, analyst, and data administration teams, to make iterative deployments with full visibility and change tracking.
• Ensures documentation of data models, transformations, and orchestration remain current, comprehensive, semantically precise, and accessible to all staff.
• Partners with others across the data management team to collaborate with business stakeholders, ensuring that pipelines are optimized for quality, reliability, contextual accuracy, and actionability.
• Plays a key role in enterprise data architecture design and analysis, including interactions with consultants and contractors.
• Monitors data systems and flows, utilizing automated tooling to ensure successful and reliable pipelines.

• A Bachelor’s degree is required, preferably in Computer Science, Software Engineering, Systems Engineering, Data Science, or another field closely related to data engineering.
• Demonstrable experience with the Snowflake platform and related tooling, e.g., dbt and Fivetran, is required. Currency in the evolution of Cortex Code (CoCo) and Semantic Views is highly desirable.
• At least 3 years of experience designing and developing data pipelines in modern data engineering environments is required. Experience working with large-scale (1M+ records) customer and behavioral data models and systems, e.g., “Customer 360” models highly desirable.
• Experience with multiple techniques for modeling and transformations, e.g., ETL, reverse ETL, and modern ELT techniques/platforms, as well as real-time/streaming processes, e.g., Apache Kafka.
• Strong understanding of all stages of integrated, data lakehouse-oriented architectures, from ingestion to semantic modeling to delivery/activation.
• Deep experience with core data engineering coding techniques/languages: SQL, Python.
• Experience working within multiple large-scale API-based, cloud architectures, e.g., Amazon AWS-based and Microsoft Azure-based is highly preferred.
• Excellent oral and written communication skills are essential to interact with all levels of College staff, members, and external resources in both group and one-on-one settings.

ACP offers a competitive salary, superior benefits and a supportive work environment. Learn more and apply online at: https://www.acponline.org/working_at_acp/jobs/.