Data Engineer / MLOps Specialist (W2-Only) | 4-8 Year of Exp

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Clarkstech, is seeking the following. Apply via Dice today! • Location: Alpharetta, GA or Berkeley Heights, NJ • Work Mode: Hybrid (Onsite 2 3 days per week) • Employment Type: Contract (W2 only No C2C) • Duration: Multi-year engagement, extended annually <>About the Role We are seeking a seasoned Data Engineer with strong MLOps expertise to join our team in either Alpharetta, GA or Berkeley Heights, NJ. This is a hybrid onsite role on ClarsTech s Payroll. Only genuine, mid-senior-level and senior level profiles will be considered candidates must demonstrate hands-on financial data domain expertise with 4-8 years of proven experience. <>Key Responsibilities • Architect and optimize large-scale data pipelines supporting financial data and ML workloads. • Perform feature engineering, model training, deployment, and tuning for enterprise-grade ML models. • Deliver cloud-native ML solutions leveraging AWS ML ecosystem (SageMaker, EMR, Glue, Lambda, etc.). • Oversee the end-to-end ML lifecycle, from algorithm selection to optimization and monitoring. • Implement real-time MLOps pipelines, addressing model drift, retraining, and inferencing strategies. • Work with distributed frameworks (Ray, Spark, Snowflake) to scale pipelines and models on datasets ranging from hundreds of millions to 1B+ records. • Collaborate closely with data scientists, architects, and business stakeholders in the financial services domain. • (Optional/Nice-to-have) Support initiatives in Generative AI, RAG, and agentic AI workflows. <>Required Qualifications • 6+ years of professional experience as a Data Engineer / MLOps Engineer in enterprise environments. • Strong Python expertise with a proven track record in ML algorithms and model development. • Deep experience building and scaling ML models on AWS machine learning services. • Hands-on expertise in handling large-scale datasets (100M 1B+ records). • Proven skills in Ray, Spark, and Snowflake for distributed data processing. • Strong foundation in data engineering and feature engineering. • Expertise in MLOps best practices: CI/CD for ML, model deployment, drift detection, retraining automation. • Domain expertise in financial data must have worked on ML/data engineering projects in financial services, banking, or capital markets. • Ability to work in hybrid setup (2 3 days onsite weekly). Nice-to-Have Skills • Knowledge of Generative AI, RAG, and agentic AI workflows. • Experience in high-frequency trading, fraud detection, or large-scale risk modeling. <>Engagement Rules Contract Position (W2 only) No C2C, No Agencies. • This is a senior-level role requiring 6+ years of professional experience in data engineering and financial services. • Candidates must have verifiable project experience in financial data and MLOps. • H1-B transfer available for the right candidate. • Multi-year contract with annual extensions. • Hybrid onsite role (Alpharetta, GA or Berkeley Heights, NJ).