Data Engineer

Location Parsippany, NJ – Office based, Hybrid position with approximately 5% travel. Job Summary The candidate will play a critical role in the development of an advanced‑analytics enabled enhancement of Zoetis’ go‑to‑market sales strategy. The candidate will be responsible for shaping the core data capabilities that drive critical use cases within the organization, such as revenue generation tactics and strategies to detect and prevent potential customer defection. The candidate will also support data quality and governance initiatives such as master data management, and assist the data engineering team in applying advanced analytics to both internal and external data sources to solve complex business problems. The role will provide the candidate with an exceptionally broad view of every aspect of Zoetis’ business, while serving as critical support for the US Petcare division. To be successful, the ideal candidate will demonstrate an advanced technical expertise, along with a thirst for knowledge and natural curiosity to enable rapid learning of the Zoetis business model and data infrastructure at a scale to support a growing $2B region. The position involves working with structured and unstructured real‑world data, requiring a candidate who is comfortable thinking independently about solving business problems. Candidates must be self‑motivated, detail‑oriented, have the ability to work with limited supervision, and must be comfortable in an environment of changing priorities. Candidates should have a strong business acumen, with evidence of delivered business value, preferably in a commercial setting. Responsibilities Design, develop, test and implement database solutions related to optimal data pipeline architecture and infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL Server, Oracle, Sales Force, Python and Big Data technologies. Develop, construct, test and maintain US commercial data layers to enable modeling. Collaborate with and enable data scientists on the team to rapidly iterate on model building and deployment. Assist in data quality, integrity, and documentation efforts in support of data governance initiatives. Automate processes that increase productivity for the US commercial data and analytics team. Develop and implement controls to ensure data integrity and regulatory compliance (SOX). Package and support deployment of releases of new code within our Azure environment. Drive innovation within the group in areas including development efficiencies within Databricks, and leading‑edge industry concepts and developments. Monitor the production schedule and provide support to remediate job failures. Provide support to team members when they need a solution to a complex issue. Provide production support to business users. Qualifications Masters from an accredited college/university in Computer Science, Information Technology, Electrical Engineering, or related field. Minimum of Three years of professional experience working as a Data Engineer. Deep experience building deployed data pipelines / ETL. Expertise in designing, building and maintaining large‑scale databases. Deep acuity in leveraging the latest in big data and cloud infrastructure methodologies. Demonstrated ability to learn and apply new concepts and technologies. Experience working directly with data scientists to build and deploy predictive and optimization models, including assisting in feature engineering. Excellent interpersonal, written, and verbal communication skills; demonstrated ability to effectively communicate complex ideas to both technical and non‑technical audiences. Fluency in English required. Expertise in database design, creation, and maintenance. Technical Skills Hands‑on experience in latest data infrastructure technologies, including cloud‑based (e.g. Amazon S3, Redshift, Azure Storage) and distributed file systems (HDFS). Strong proficiency in SQL and at least one programming language (Python, Scala, Java). Experience in working with modern ETL tools and data pipeline platforms (e.g., Databricks, Azure Data Factory, Airflow, DBT, Prefect). Experience in large‑scale/distributed computing and analytics (Hadoop, Spark). Familiarity with predictive model building in Python (Pandas/PySpark) / R. Experience with source control and collaboration tools (e.g. Git). Software development / engineering experience a plus. Experience in scaled model testing, integration, and deployment (DevOps) a plus. Experience working in Microsoft tech stack preferred. Salary and Benefits The US base salary range for this full‑time position is $105,000 - $151,000. The range displayed on each job posting reflects the base pay target range for new hire salaries for the position. Within the range, individual pay is determined by work location and additional factors, including job‑related skills, experience, and relevant education or training. In addition to compensation, Zoetis offers a comprehensive benefits package that supports the physical, emotional and financial well‑being of our colleagues and their families including healthcare and insurance benefits beginning on day one, a 401(k) plan with a match and profit‑sharing contribution from Zoetis, and 4 weeks of vacation. Equal Opportunity Statement Zoetis is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status or any other protected classification. Disabled individuals are given an equal opportunity to use our online application system. We offer reasonable accommodations as an alternative if requested by an individual with a disability. Authorization and Sponsorship All applicants must possess or obtain authorization to work in the US for Zoetis. Zoetis retains sole and exclusive discretion to pursue sponsorship for the acquisition or maintenance of non‑immigrant status and employment eligibility, considering factors such as availability of qualified US workers. Individuals requiring sponsorship must disclose this fact. #J-18808-Ljbffr