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If you are a Data Engineer looking for excitement, challenge and stability in your work, then you would be glad to come across this page.

We are an IT Solutions Integrator/Consulting Firm helping our clients hire the right professional for an exciting long term project. Here are a few details.

Check if you are up for maximizing your earning/growth potential, leveraging our Disruptive Talent Solution.

Requirements Position Title: Data Engineer Location: Onsite – 5 days/week in New York, NY or Boston, MA Duration: 6–12 Months Contract Experience Level: 5+ Years About the Role: We are seeking a highly skilled Senior Data Engineer to design, build, and optimize scalable data architectures that power analytics, machine learning, and enterprise applications. You will work closely with cross-functional teams, applying your expertise in SQL, Snowflake, Python, and cloud-native tools to deliver high-quality, secure, and efficient data solutions in a fast-paced financial services environment.

Key Expertise Required (Top Priorities): Deep knowledge of data modeling and data architecture for enterprise-scale applications.

Strong understanding of ML Ops and how it leverages data to deliver predictive and AI-driven outcomes.

Proven experience implementing data architectures that support data science models, including prediction, machine learning, and advanced analytics.

Core Responsibilities: Data Architecture & Modeling: Design, implement, and maintain enterprise-grade data architectures, ensuring optimal performance, scalability, and reliability.

ELT Development: Build robust ELT frameworks using DBT, MWAA, and Snowflake from the ground up.

SQL & Snowflake Expertise: Write optimized SQL queries, perform performance tuning, and implement best practices in data modeling.

Python Development: Develop automation scripts, data integration pipelines, and REST API connectors using Python.

Workflow Orchestration: Leverage Apache Airflow for scheduling, orchestration, and monitoring of data workflows.

Cloud Integration: Work with AWS services (S3, Lambda, IAM, CloudWatch) to manage data pipelines, security, and monitoring.

Data Quality & Governance: Implement processes to ensure accuracy, consistency, and compliance with enterprise data governance and security policies.

ML Ops Integration: Architect data flows that enable machine learning models, prediction systems, and RAG (Retrieval-Augmented Generation) workflows.

Collaboration & Agile Practices: Partner with UX teams, participate in design discussions, code reviews, and Agile ceremonies to continuously improve deliverables.

Security & Compliance: Follow best practices for secure coding, access control, and compliance—especially for financial data systems.

Required Skills & Experience: 5+ years of professional experience as a Data Engineer.

Strong SQL and Snowflake skills, including performance tuning and advanced data modeling.

Proven track record in building (not just consuming) ELT frameworks using DBT and MWAA.

Proficiency in Python for automation, scripting, and REST API integrations.

Hands-on experience with Apache Airflow for orchestration and workflow monitoring.

Expertise with AWS services including S3, Lambda, IAM, CloudWatch.

Experience in integrating and processing data from REST APIs.

Understanding of data quality, governance, and cloud-native troubleshooting.

Exposure to RAG workflows and data-driven ML model enablement.

Familiarity with Agile or Scrum methodologies.

Preferred Qualifications: Experience in financial services or other highly regulated industries.

Strong understanding of secure coding practices and compliance frameworks.

Hands-on ML Ops pipeline development and deployment experience.

Benefits Visit us at http://alignity.io/careers. Alignity Solutions is an Equal Opportunity Employer, M/F/V/D.

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