Principal Data Engineer

Curate Partners United State
Visa Sponsorship
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AI Summary

Design and enhance enterprise-grade data platforms, build and maintain scalable data pipelines, and lead technical design reviews. Requires 7+ years of experience in data engineering or data platform development. Strong proficiency in SQL, Python, and large-scale data processing frameworks such as Apache Spark or PySpark.

Key Highlights
Design and enhance enterprise-grade data platforms
Build and maintain scalable data pipelines
Lead technical design reviews
Key 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
Technical Skills Required
SQL Python Apache Spark
Benefits & Perks
H1B sponsorship
Hybrid work arrangement
3 days/week in Woburn or Westborough

Job Description


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 Databricks environment.

• 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 databricks platform from greenfield/scratch

• Then move their Legacy Oracle platform onto the databricks 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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