Top Data Engineer Jobs in Boston, MA

Provide pre-sales technical leadership for data management and analytics solutions: assess customer needs, design and validate cloud data architectures (warehouses, lakehouses, ETL/ELT, RAG/GenAI), build demos/POCs, and support sales with presentations, integration planning, and technical guidance.

As a Senior Data & Analytics Engineer, you'll lead data initiatives, manage a team, and ensure data quality while turning insights into actionable decisions across the company.

The Data Engineer will manage data extraction pipelines, modernize data systems, implement monitoring tools, optimize workflows, and support compliance requirements using various tools and platforms.

Design, build, and maintain production data pipelines and the unified data model using Snowflake, dbt, and orchestration tools. Optimize, test, document, and monitor ELT workflows, enforce engineering best practices, mentor teammates, and deliver trustworthy data products for analytics and business decisions.

Architect, build, and maintain scalable ELT data pipelines and analytics-ready data marts. Lead dbt modeling, ensure data quality, CI/CD, and documentation. Partner with stakeholders, mentor junior engineers, evaluate tooling (reverse ETL), and drive long-term data platform strategy.

Design, build, and maintain production data pipelines and tooling (CI/CD, testing, validation) using Snowflake, dbt, and orchestration tools. Model, transform, document, and optimize data to produce reliable curated datasets for analytics and solutions, enforce engineering best practices, and mentor teammates while ensuring scalability, observability, and data integrity.

Design and maintain scalable, secure data pipelines and contracts for cloud and on-prem environments. Implement real-time processing and observability tooling, collaborate with product teams, and support asset visibility workflows for OT/ICS customers.

Lead design, build, and support of cloud-based ETL, data warehousing, and reporting solutions. Develop/optimize ETL pipelines, data models, and queries; deploy containerized services on Kubernetes; automate workflows; mentor teammates; collaborate with architects, data scientists, and stakeholders to deliver scalable analytics and reporting products.

Design, build, and scale data pipelines and integrations for the TDX platform. Implement REST API integrations, ingest and unify customer data, optimize pipelines for performance and quality, ensure data security and governance, and collaborate with Product, Data Science, and customer teams to deliver reliable analytics-ready data.

Design and maintain ELT pipelines, build dimensional (star/snowflake) analytics models, implement data transformations and quality checks, document data lineage and governance, partner with BI users, and mentor junior engineers to deliver performant analytics for business reporting and KPIs.

As a Senior Data Engineer, you'll manage and optimize data infrastructure for a healthcare project, ensuring reliability and performance of data systems while developing new capabilities.

Design, build, and operationalize large-scale data platforms and pipelines on GCP. Mentor engineers, ensure data quality and system performance, and deploy production data solutions using BigQuery, Dataflow, Airflow, Terraform, and related tools.

Implement client revenue cycle data into company systems by creating and configuring ETL processes, building data transformations and logical/physical schemas, documenting solutions in Jira, attending client meetings, and mentoring team members to ensure post-implementation data integrity.

Design, build, and maintain scalable ETL/ELT pipelines and Power BI dashboards; write testable Python, R, and SQL code; enforce version control and engineering standards; partner with data scientists to productionize analytics; explore AI tools; and mentor junior staff.

Lead end-to-end enterprise data migrations and consolidations from legacy ERPs to cloud platforms. Design cloud architecture, build automated ETL/ELT pipelines and ontology-driven schemas, implement CDC and validation frameworks, deliver dashboards and migration controls, advise executives, and develop reusable accelerators while mentoring teams and enabling client post-migration governance.

The role involves building and optimizing data pipelines, modeling datasets, applying machine learning techniques, and supporting data strategies. Candidates should have experience with Python, data lakes, warehousing, and related technologies.

Design and deploy scalable data infrastructure and models, maintain CDC pipelines, build reporting tools and dashboards, write high-performance SQL, partner with product and engineering to enable enterprise-wide analytics and data-driven decision making.

The Data & Analytics Engineer will model and serve data, improve architecture, and collaborate with teams to sustain the data strategy, requiring 5+ years of experience.

The Senior Data Engineer will manage and transform data pipelines, implement changes in Snowflake, monitor costs, and resolve data issues.

Nagarro seeks an Associate Principal Engineer in Big Data to leverage extensive IT experience for strategic organizational value. The role values self-starters and innovation.

The Senior Data Engineer will design and build data pipelines for usage and revenue reporting, manage Snowflake as the enterprise data warehouse, and collaborate with Finance to ensure data accuracy and quality.

As a Lead Data Engineer, you'll optimize data workflows, manage data engineering projects, mentor junior engineers, and ensure robust data solutions meet business needs.

Design, build, and operate scalable batch and streaming data pipelines; partner with customer and product teams to implement health system integrations; improve monitoring, tooling, and data accessibility; serve as a dataset and tooling subject matter expert.

Technical leader building scalable data pipelines, analytics infrastructure, and APIs. Own architecture, optimize large-scale query performance, mentor engineers, and partner with product and integration teams to deliver real-time and historical analytics.

Design, build, and operate cloud-native data platforms and scalable pipelines using Snowflake and dbt. Lead orchestration, CI/CD, observability, and performance tuning. Collaborate on backend services and limited frontend work, mentor engineers, define modeling standards, and participate in multi-team architecture and system design.