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

  • Berkeley Heights, NJ
  • Posted 1 day ago | Updated 1 day ago

Overview

Hybrid
$80,000 - $140,000
Full Time
No Travel Required

Skills

SageMaker
EMR
Glue
Lambda
Ray
Spark
Snowflake
MLOps
Python
AWS

Job Details

  • 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).
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