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Principal Data Engineer

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Onsite

Principal Data Engineer

Curate Partners

Principal Data Engineer

Skills

Google Cloud PlatformSQL QueriesData EngineeringPythonData ScienceKafkaSnowflakeDatabricksGitData AnalysisMachine LearningAIAWSOraclePySparkApache AirflowAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Woburn, MA, USA

Work mode:

Onsite

Published on:

31 August 2026

What they need


Principal Data Engineer

Logistics:

  • Full-time
  • Hybrid in Westborough, MA or Woburn, MA 3 days/week
  • This role DOES offer H1B sponsorship if you already hold a valid H1B visa.

Top things the team is looking for:

  • Building Pipelines in a Snowflake environment. Very strong SQL and Medallion experience.

  • Data Architect/Modeler experience is most important, Data Engineering is second. Need an expert Data Modeler to help their end users.

  • Need someone who can help them use and choose the right AI to build autonomous agents for Data Engineering workflows

  • Excellent communication skills – this person needs to showcase what they are building and doing to the business

  • 7+ years of experience

  • Someone local who can be onsite 3 days/week in Woburn or Westborough. The team does a lot of whiteboarding together and in-person is what’s best.

What they are doing:

  • Striving for accurate data with excellent performance and accuracy.

  • Loading data into schemas/tables and improving them and dashboards through better efficiency/speed for the business to consume

  • Improving the data pipelines delivered to the business

  • Automate their processes with AI – what are the right tools, agents etc.

  • Build a snowflake platform from greenfield/scratch

  • Then move their Legacy Oracle platform onto the snowflake platform. Need strong Migration experience!

Responsibilities

  • Design and enhance enterprise-grade data platforms, including ingestion, transformation, storage, orchestration, and data serving layers for both batch and streaming use cases
  • Build and maintain scalable data pipelines, reusable frameworks, and enterprise data models to support analytics, artificial intelligence, and operational reporting
  • Define and manage semantic data layers while implementing governance controls such as data quality validation, lineage tracking, metadata management, and secure access
  • Establish engineering standards for development, testing, version control, documentation, and continuous integration and delivery practices
  • Optimize data solutions for cost efficiency, scalability, and performance using modern engineering and operational practices
  • Lead technical design reviews, incident response activities, and root cause analysis to improve platform stability and reliability
  • Collaborate with data science teams to deploy and operationalize machine learning models for batch and real-time use cases
  • Partner with cross-functional teams including analytics, security, and architecture to deliver compliant, high-quality data solutions
  • Evaluate new technologies and guide architectural decisions, including build-versus-buy considerations
  • Mentor engineering teams through technical guidance, code reviews, and knowledge sharing to raise overall engineering standards
  • Promote consistency and reuse across distributed teams by sharing best practices and standardized components

Required Experience and Skills

  • Bachelor’s degree in computer science, statistics, applied mathematics, or a related quantitative field
  • At least 8 years of experience in data engineering or data platform development, including significant experience in senior or principal-level roles
  • Strong proficiency in SQL, Python, and large-scale data processing frameworks such as Apache Spark or PySpark
  • Hands-on experience with major cloud platforms such as AWS, Azure, or Google Cloud, along with modern data platforms such as Databricks or Snowflake
  • Experience with streaming technologies such as Apache Kafka or similar tools and orchestration frameworks such as Apache Airflow
  • Strong background in data modeling, including dimensional, data vault, and domain-oriented approaches
  • Experience implementing data governance frameworks, including quality controls, lineage tracking, metadata management, and access controls
  • Knowledge of software engineering practices including CI/CD, infrastructure as code, and automated testing
  • Proven ability to lead complex technical initiatives, influence stakeholders, and guide engineering teams
  • Strong communication skills with the ability to present technical concepts clearly and effectively
  • Ability to manage multiple priorities and work effectively in fast-paced environments

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