Data Engineer

Equifax is searching for an innovative Intermediate Data Engineer to join our Global Keying & Linking group. In this role, you will be a key contributor to a team dedicated to advancing data quality, data analysis, operational innovations, data onboarding, and feature design and testing. You will leverage your coding experience to solve complex data challenges, build in-depth data quality assessments, and drive improvements in data onboarding and K&L feature design. Equifax has a hybrid work schedule that allows for two days of remote work (Monday and Friday) with 3 days onsite (Tuesday thru Thursday) every week. This role reports to our office Alpharetta, GA office. Note: This position does not offer immigration sponsorship (current or future) including F-1 STEM OPT extension support. This is a direct-hire role and is not open to C2C or vendors. What You'll Do With moderate supervision, manage project's progress, metadata collection, development and management. Perform investigations on internal / external stakeholder queries with high level direction from the Team Leader. Analyze problems, identify root cause, formulate findings and observations of results, suggest resolutions and communicate to internal / external stakeholders with moderate guidance from the Team Leader. Maintain current knowledge of industry regulatory requirements such as reporting mandates, concepts and procedures, compliance requirements, and regulatory framework and structure. Be able to support internal/external queries on data standards. Perform intermediate level data quality checks, following established procedures. What Experience You Need BS degree in a STEM major or equivalent discipline; Master's Degree strongly preferred. 2 years of experience as a data engineer or related role. Cloud certification strongly preferred. Intermediate skills using programming languages such as Python, SQL or scripting languages. Basic understanding and experience with Google Cloud Platforms and an overall understanding of cloud computing concepts. Experience building and maintaining simple data pipelines, following guidelines, transforming and entering data into a data pipeline in order for the content to be digested and usable for future projects. Experience with data analytics and Big Data. Experience analyzing problems, results, and making observations and conclusions from data analysis. What Could Set You Apart Background or practical experience in Data Science, including familiarity with statistical analysis, predictive modeling, or machine learning concepts. Experience with Entity resolution is highly preferred. Demonstrated experience designing, building, or maintaining agentic AI workflows and solutions using Large Language Models (LLMs). Hands-on experience utilizing AI coding tools (e.g., GitHub Copilot, Gemini) to accelerate development, problem-solving, and code optimization. Exceptional analytical thinking paired with a deep, practical understanding of data quality principles, data profiling, and anomaly detection. A highly adaptable, resourceful, and intellectually curious mindset with a strong willingness to learn and receive coaching. Excellent communication and interpersonal skills, with the ability to effectively collaborate with cross-functional teams and translate complex data concepts for both technical and non-technical stakeholders. #J-18808-Ljbffr Socket