Top Data Engineer Jobs in Boston, MA

The Data Engineer role involves developing and maintaining data pipelines for forecasting in commercial real estate, ensuring data integrity and supporting analytics teams.

As a Senior Data Engineer at Jellyfish, you'll build and maintain data pipelines, optimize orchestration, automate CI/CD processes, and enhance data integration while ensuring high performance and reliability.

The role involves architecting and improving data systems, defining governance standards, optimizing performance, and mentoring engineers in data engineering.

Lead the evolution of data platform by designing scalable pipelines, improving data processes, mentoring teams, and modernizing data architecture.

Design, build, and manage large-scale data structures, pipelines, and ETL workflows. Integrate data for analytics and Data Science, optimize Hadoop/HDFS processes, develop data marts and models, ensure data quality and accessibility, and evaluate/adopt tooling for real-time and offline processing.

The Data Engineer will develop data pipelines, support automation, and collaborate within an Agile team to manage complex data sets, ensuring performance and reliability in data processing.

Build and maintain scalable, governed data pipelines from ingestion through transformation and integration. Implement schema validation, data quality checks, job monitoring, and production-grade APIs. Work with Python, SQL, Airflow, dbt, AWS (EMR, Athena, S3), Iceberg/Parquet, and contribute to CI/CD, observability, and on-call support while collaborating with analytics and product teams.

The Senior Staff Data Engineer will design scalable data systems, lead technical direction, optimize data platforms, and ensure data quality and performance for Observability & Insights.

Build user-facing data products by transforming internal data into actionable metrics. Collaborate with platform teams and data scientists to prototype, validate, and prioritize data sources. Write requirements and proposals, engage in user research, and deliver performant Python/SQL-based data features using Databricks and Postgres.

Lead design and development of web UI and REST middleware within an Agile team. Define requirements and acceptance criteria, implement Java/Spring and Angular solutions, build CI/CD pipelines, work with Product Owner and testers, and produce/update design documentation.

In this role, you'll build and scale high-throughput data pipelines, ensure data quality, and leverage AI for improved data operations. You'll also lead initiatives in a fast-paced environment focused on real estate data engineering.

The Data Engineer will modernize and stabilize the data platform, optimize ELT/ETL pipelines, ensure data quality, and collaborate on AI architecture.

As a Data Engineer, you will build and optimize data pipelines, manage ETL workflows, and ensure efficient data access and quality within the infrastructure.

The Data Engineer will develop and maintain data pipelines, build data models, ensure data quality, and support cross-functional teams while improving internal data platform infrastructure and documentation.

Design, build, and maintain end-to-end batch and streaming data pipelines; develop ETL/ELT workflows and modular Python code; write and optimize SQL; implement analytics data models; monitor data quality, troubleshoot failures, and document pipelines; collaborate with stakeholders and mentor teammates. Remote role for candidates based in Latin America.

As a Data Engineer, you will develop and manage data pipelines, ensuring reliable data ingestion and delivery while optimizing for simplicity and performance.

Design, build, and maintain scalable ETL/ELT data pipelines on Databricks and AWS S3; manage large geospatial and temporal datasets; productionize ML models; implement data validation, testing, and monitoring; optimize storage and processing; document workflows; collaborate cross-functionally.

The Data Engineer role involves designing and maintaining AWS-cloud-native data systems, developing ETL processes, optimizing data pipelines, and ensuring data security and governance in healthcare data applications.

The Data Engineer at Anteriad will design, build, and optimize data pipelines, manage data integration processes, support analytics efforts, and collaborate with stakeholders to deliver scalable data solutions.

Design, build, and maintain data pipelines and lakehouse infrastructure from ingestion through curated gold-layer objects. Monitor and resolve pipeline failures, implement data governance and quality, migrate on-prem to cloud, collaborate with BI and engineering teams, and automate/optimize ETL/ELT processes to support analytics and reporting.

We are seeking a Data Engineer to design, build and optimize scalable data pipelines. Strong experience in Databricks, PySpark, and data warehouse concepts is required.

As a Senior Data Engineer, you will manage data integration, optimize performance, mentor junior engineers, and collaborate with product teams on innovative solutions in healthcare data modeling.

Design, build, and maintain scalable Spark-based ETL pipelines and computed tables in a central data lake. Integrate structured and unstructured IoT, sensor, and external data for analytics, model training, and dashboards. Collaborate with Data Science, Analytics, and ML teams to ensure reliable, high-quality customer-facing datasets.

Design, build, and maintain large-scale data structures, ETL pipelines, and data models on cloud platforms (GCP/BigQuery, AWS, Azure). Collaborate with Data Science to integrate models, ensure data quality, troubleshoot systems, and support analytics modernization.

Design, build, and manage large-scale data structures, pipelines, and ETL workflows. Develop real-time and batch processing, integrate data for analytics and ML, collaborate with Data Science to productionize models, ensure data quality and accessibility, and recommend tools and architectures for scalable data solutions.