Data Engineer

Zoetis•Parsippany-Troy Hills, NJ

13d•$105,000 - $151,000•Hybrid

About The Position

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. This 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.

Requirements

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
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

Nice To Haves

Software development / engineering experience a plus
Experience in scaled model testing, integration, and deployment (DevOps) a plus
Experience working in Microsoft tech stack preferred

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
Assists 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.