Sr. Data Analytics Engineer

City: Glendale, CA Onsite/ Hybrid/ Remote: Onsite (4 days a week) Duration: 12 months Rate Range: Up to$96/hr on W2 depending on experience (no C2C or 1099 or sub-contract) Work Authorization: GC, USC, All valid EADs except OPT, CPT, H1B Must Have: • Strong SQL and Python programming skills • Experience with data pipeline development and orchestration tools (e.g., Airflow, dbt, or similar) • Proficiency in cloud data platforms (AWS, GCP, or Azure) • Knowledge of data modeling, ETL, and data warehousing concepts • Experience integrating analytics and machine learning workflows Responsibilities: • Architect and design scalable data products and foundational datasets. • Develop and maintain high-quality, efficient code for data products. • Collaborate with stakeholders to define data strategies and understand business requirements. • Create specifications for data ingestion, transformation, and quality standards. • Document and train teams on data product usage for automation and reporting. • Build and optimize data pipelines to automate deployment of analytical and machine learning models. • Monitor, evaluate, and improve statistical and ML models used in analytics products. • Partner with data scientists and engineers to translate methodologies into production-ready solutions. • Coordinate with cross-functional technology and business teams to ensure alignment and delivery. Qualifications: • Bachelor’s or Master’s degree in Computer Science, Data Engineering, Statistics, or a related field. • 5+ years of experience in analytics engineering or data engineering. • Strong understanding of database systems, data integration, and transformation best practices. • Experience deploying and maintaining cloud-based data pipelines and analytics solutions. • Excellent communication and collaboration skills, with a focus on data-driven decision-making.