Data Engineer (Hybrid)

The Data Engineer (Hybrid) is responsible for transforming data into a format that can be easily analyzed through the design and implementation of methods to improve data reliability and quality. They will combine raw information from various sources to create consistent and machine-readable formats. In addition to develop, maintain, and test infrastructures for data generation, extraction, and transformation for predictive modeling.

Duties & Responsibilities:

Build the infrastructure required for optimal extraction and transformation from a wide variety of data sources. Build and optimize 'big data' pipelines, architectures, and datasets to be used across the organization. Understand and translate complex business priorities into clearly defined technical/data specifications for implementation. Support other team members on data initiatives and ensure optimal data delivery architecture consistency throughout ongoing projects. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. Implement processes and systems by coding, testing, and debugging to monitor data quality, and ensure accuracy of production data. Collaborate with analytics and business teams to improve data models that feed business intelligence tools to increase data accessibility and fostering data-driven decision making across the organization. Work closely with business architecture, IT, and analytic teams to help implement an end-to-end data strategy from data ingest to output into business tools. Work with Modeling Analyst to data mine and extract key identifiers coming from unstructured, free format datasets. Collaborate across multiple business functions to combine several aspects (such as rating and competition) of predictive modeling results into one analytical dashboard. Expand knowledge in multiple programming languages and software. Monitor developments in data transformation and storage to remain current with respect to new approaches and methods utilized within the data science industry. Complete internal and external coursework to further develop programming skills and business knowledge. Other duties as assigned.

Requirements:

Bachelor's degree in computer science, statistics, math, or related field or equivalent combination of education and experience. 2 years of experience in a data science and/or programming related field. Work experience with relational databases and query authoring. Experience supporting and working with cross-functional teams in a dynamic environment. Experience developing data pipelines for warehouses/lakes.

Qualifications & Skills:

Basic knowledge of business processes and analytical support systems. Basic knowledge of Radar or similar software. Advanced working knowledge of analytical tools including SQL, SAS, Python and/or R. Working knowledge of big data tools such as Databricks, Apache Spark, and Hadoop Strong project management and organizational skills. Strong coding skills. Analytical with the ability to distill, structure, and draw insight from large amounts of data. Strong problem-solving skills. Ability to deal with ambiguity and operate in a fast-paced and rapidly changing environment with competing project priorities. Self-directed, forward thinking, ability, and desire to learn. Comfortable supporting data needs of multiple teams, systems, and products. Ability to communicate clearly, effectively, and concisely, both verbally and in written form. Ability to work in an open team environment. Ability to foster relationships with peers

Market Range:

13 / Exempt / 40 hours per week / Hybrid - 2 Days in

Office Salary:

$79,756 - $132,926 Accepting applications until: 4/30/26