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Data Engineer - Snowflake / AWS / ML Ops

Data Engineer - Snowflake / AWS / ML Ops

AlignityBoston, MA, United States
13 days ago
Job type
  • Temporary
Job description

Job Description

Do you love a career where you Experience , Grow & Contribute at the same time, while earning at least 10% above the market? If so, we are excited to have bumped onto you.

Learn how we are redefining the meaning of work , and be a part of the team raved by Clients, Job-seekers and Employees.

  • Jobseeker Video Testimonials
  • Employee Glassdoor Reviews

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 Alignity Solutions is an Equal Opportunity Employer, M / F / V / D.

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    Clients Testimonial : Click Here

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