Data Analytics Engineer - Local Only

Our direct client is looking for a Data Analytics Engineer for a 1-year contract to work Hybrid 3 days week, onsite in San Diego, CA. Local candidates Only, must work 3 days onsite. Data Analytics Engineer who brings deep expertise in data analysis, data wrangling, and insights generation, complemented by working knowledge of predictive analytics and solid software engineering skills. This role focuses on turning complex, multi-source data into trusted, decision-ready insights; building scalable analytics pipelines; and applying predictive techniques where they add measurable business value. Data Analytics Engineer • 12month Contract • Monday – Friday, 40 hour work week. • Location: San Diego, CA ( Carmel Valley/ Del Mar Hights area) • Hybrid, 3 days week onsite - (Onsite, Tuesday, Wednesday, Thursday) • Contract is open for 1099 or Corp-2-Corp contract only. Local candidates, In-Person Interview is required Skills & Qualifications • Strong proficiency in Python and SQL for data wrangling, analytics, and statistical analysis. • Experience with BI and visualization tools – Power BI and Tableau required • Ability to work with business SMEs and elicit requirements and document them independently • Demonstrated experience in advanced analytics, KPI development, and insight generation. • Working knowledge of predictive analytics and machine learning techniques using libraries such as Scikit-learn or XGBoost. • Solid understanding of software development principles, data modeling, and version control (Git). • Bachelor’s degree in Computer Science, Data Analytics, Statistics, Engineering, or a related field. Preferred Qualifications • Experience operationalizing analytics or predictive models using MLOps or analytics lifecycle tools (e.g., MLflow). • Familiarity with cloud data platforms (Azure OneLake, MS Fabric, AWS Redshift, Azure Synapse). • Exposure to data governance, data quality, and security best practices in enterprise environments. • Work experience in Life Sciences (like: biotechnology, pharmaceuticals, and medical devices) Key Responsibilities Advanced Data Analytics & Predictive Insights • Perform complex data wrangling, cleansing, normalization, and transformation across diverse structured and semi-structured data sources. • Lead exploratory and diagnostic data analysis to surface trends, anomalies, drivers, and root causes underlying business performance. • Develop and maintain metrics frameworks, KPIs, and analytical models that support operational, financial, and strategic decision-making. • Partner with business stakeholders to translate ambiguous questions into clear analytical hypotheses, analyses, and insights. • Design and deliver dashboards, reports, and analytical narratives that clearly communicate insights to technical and non-technical audiences. • Apply predictive and statistical modeling techniques (e.g., regression, classification, time-series forecasting) to support forecasting, scenario analysis, and optimization use cases. • Validate analytical outputs through sanity checks, data quality assessments, and peer review to ensure accuracy and trustworthiness. Software Engineering & Analytics Pipeline Development • Design, build, and maintain ETL/ELT pipelines that support analytics, reporting, and predictive use cases. • Implement scalable and reusable analytics code and data models using Python, SQL, and cloud-native services. • Optimize data pipelines and analytical workflows for performance, reliability, and maintainability. • Apply software engineering best practices, including version control, testing, CI/CD, and documentation. • Automate recurring analytics processes and model refreshes to reduce manual effort and improve consistency. If you are interested, please send me your updated Word Resume, along with your direct phone number and email.