Data Engineer

Boston, Massachusetts, United StatesOnsiteFull TimePosted 2 months agoVisa sponsorship available

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Role summary

Studentslanding is seeking a full-time, on-site Data Engineer in Boston, MA, to build and maintain data pipelines, develop data models, and optimize ETL processes. The role involves managing data warehouses, implementing real-time data processing, and ensuring data quality in regulated environments. Responsibilities include architecting scalable data solutions, leading data migrations, and enabling self-service analytics. The ideal candidate will have a Master's degree in a related field, strong proficiency in Data Engineering and Data Modeling, and experience with data warehousing and real-time systems. Cloud platform experience is preferred.

Company Description

Welcome to Studentslanding! We are dedicated to empowering learners by delivering innovative solutions that support academic and professional growth. Based in Boston, MA, our team focuses on creating impactful tools and platforms designed to make education more accessible and effective. We aim to foster a diverse, inclusive environment where every team member contributes to our mission of transforming education for the b

etter.

Role Description

This is a full-time, on-site role for a Data Engineer based in Boston, MA. The Data Engineer will be responsible for building and maintaining data pipelines, developing and managing data models, implementing and optimizing ETL processes, and maintaining data warehouses. The role will also involve collaboration with analysts and engineers to ensure accurate, quality data is available for analysis and insights.

Key Responsibilities

Architect and develop scalable data pipelines and ELT frameworks using modern cloud technologies.
Design and maintain data lakes and warehouses, ensuring efficient data storage, partitioning, and schema enforcement.
Build and optimize ETL/ELT processes for high-volume structured and streaming datasets.
Develop real-time data processing systems using event-driven architectures.
Implement data quality, validation, and compliance frameworks for regulated environments.
Lead cross-region and high-availability data migrations with zero downtime.
Orchestrate complex workflows using tools like AWS Step Functions or equivalent.
Optimize data warehouse performance and cost efficiency (e.g., Redshift).
Enable self-service analytics through metadata governance and query optimization layers.
Collaborate with product managers, business analysts, and engineering teams to deliver data-driven solutions.
Apply advanced data modeling and analytics techniques to support business insights.

Required Qualifications

Master's degree in Computer Science, Data Science, or a related field.
Strong proficiency in Data Engineering and Data Modeling.
Hands-on experience with ETL/ELT pipelines and data orchestration tools.
Deep understanding of data warehousing concepts and best practices.
Experience with real-time data processing and streaming systems.
Strong analytical and problem-solving skills.
Ability to work effectively in cross-functional teams.

Preferred Qualifications

Experience with cloud platforms (AWS, GCP, or Azure).
Hands-on experience with:
AWS Glue (Apache Spark), S3, DynamoDB, Redshift
Kafka, Apache Flink
AWS Step Functions, Lambda, SQS
Familiarity with serverless architectures and event-driven systems.
Experience in data governance, compliance, or regulated environments.
Exposure to GenAI applications in data querying or analytics (e.g., Bedrock, LLM-powered query engines).

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