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 6+ years of proven experience. Fresh graduates or entry-level applicants will not be considered.

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 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.
• Entry-level applicants will not be considered.
• 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).

👉 To Apply: Submit your resume with detailed project history highlighting your financial data engineering and MLOps experience to jobs@clarkstech.com. Only genuine senior-level profiles will be reviewed and will be considered.