Data Engineer

Curate Partners; Massachusetts; Hybrid; USD 90,000 - 130,000; Full time

Job summary

Curate Partners is seeking a Data Engineer to build and optimize enterprise data pipelines in a hybrid model with onsite three days a week in the Boston area. You will work closely with data engineering, analytics, product, and business teams to deliver scalable data solutions and modernization efforts.

The ideal candidate has 2–4 years of data engineering or related experience, strong SQL, Snowflake, and Python basics, plus knowledge of data quality, orchestration, and monitoring.

Qualifications

• Bachelor’s degree in CS/IS/Engineering or related field.
• 2–4 years in data engineering or related tech discipline.
• Strong SQL and Snowflake experience; Python for data processing.

Responsibilities

• Build, maintain, and enhance data pipelines for analytics and enterprise data products.
• Develop and optimize SQL-based processes for data extraction, transformation, validation, and delivery.
• Implement data quality controls, monitoring, and validation routines for reliable data availability.
• Support pipeline automation, job scheduling, and troubleshooting across data environments.
• Collaborate with engineering, analytics, product, and business stakeholders to deliver scalable data solutions.
• Assist with data warehouse modernization and migration initiatives.
• Document data assets, metadata, pipeline workflows, and technical processes.

Skills

SQL

Python

Data analysis

Agile methodologies

Education

Bachelor’s degree in Computer Science, Information Systems, Engineering, or related quantitative field

Tools

Snowflake

Git

Airflow

Job description

We can consider candidates who are U.S. Citizens, Green Card holders, or H-1B visa holders. The role requires working onsite three days per week in the Boston Area (2 location options).

Job Description

A leading organization is seeking a Data Engineer to support the development, maintenance, and optimization of enterprise data solutions that enable analytics, reporting, and data-driven decision-making. This position will work closely with data engineering, analytics, product, and business teams to deliver reliable and scalable data pipelines, support data platform initiatives, and contribute to ongoing modernization efforts.

The ideal candidate has strong SQL expertise, experience working with enterprise data warehouses such as Snowflake, and a solid foundation in data engineering principles. Exposure to large-scale data migration initiatives, particularly data warehouse modernization efforts, is highly valued.

Responsibilities

• Build, maintain, and enhance data pipelines that support analytics, reporting, and enterprise data products.
• Develop and optimize SQL-based processes for data extraction, transformation, validation, and delivery.
• Implement data quality controls, monitoring processes, and validation routines to ensure reliable data availability.
• Support pipeline automation, job scheduling, and troubleshooting activities across data environments.
• Collaborate with engineering, analytics, product, and business stakeholders to understand requirements and deliver scalable data solutions.
• Assist with data warehouse modernization and migration initiatives.
• Document data assets, metadata, pipeline workflows, and technical processes according to established standards.
• Participate in code reviews, testing activities, and deployment processes.
• Investigate and resolve data issues, escalating risks and technical challenges when appropriate.
• Contribute to continuous improvement initiatives related to data engineering practices and platform operations.

Required Experience and Skills

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related quantitative field.
• 2 to 4 years of experience in data engineering, analytics engineering, database development, data development, or a related technical discipline.
• Strong SQL skills with experience writing complex queries for data extraction, transformation, and analysis.
• Experience working with enterprise data warehouse platforms such as Snowflake.
• Working knowledge of Python or another programming language used for data processing and automation.
• Understanding of data pipeline concepts, including ingestion, transformation, orchestration, scheduling, and monitoring.
• Exposure to cloud-based data environments.
• Familiarity with data quality processes, validation frameworks, metadata management, data lineage, and access controls.
• Basic understanding of data modeling concepts, including fact tables, dimension tables, relationships, and analytical data structures.
• Experience using source control tools such as Git.
• Ability to work within Agile or iterative development environments.
• Strong analytical, problem-solving, and organizational skills.
• Excellent written and verbal communication skills.
• Ability to collaborate effectively with both technical and business stakeholders.

Preferred Experience and Skills

• Experience supporting large-scale data migration or data warehouse modernization initiatives.
• Familiarity with Snowflake implementation, optimization, or migration projects.
• Experience with Spark, PySpark, or distributed data processing technologies.
• Familiarity with orchestration tools such as Apache Airflow, Azure Data Factory, or similar platforms.
• Exposure to cloud platforms including Azure, AWS, or Google Cloud.
• Master’s degree in Computer Science or a related quantitative field.
• Demonstrated interest in expanding expertise within modern data engineering and cloud data platforms.