Top Senior Data Engineer Jobs

Lead data engineering efforts to design, build, deploy, and maintain scalable data platforms and pipelines. Guide cross-functional teams, support ETL/ELT workflows, parse structured and unstructured data, develop scripts to convert data, and operate/monitor enterprise-scale data applications for analytics and reporting.

Design, build, and operate scalable finance data pipelines and analytics-ready datasets. Support ELT/ETL, data quality, governance, semantic models, Power BI reporting, forecasting, ARR analytics, and AI-enabled analytics. Partner with finance stakeholders to translate requirements and maintain production-grade, monitored data solutions.

Lead design, build, and maintain scalable data pipelines, ETL processes, data models, and storage solutions. Support production data ecosystem, optimize performance, ensure data quality and security, integrate data sources/APIs, and provide technical guidance to teams while collaborating with stakeholders.

Design, build, and optimize scalable Azure data platforms and lakehouse architectures. Develop ETL/ELT pipelines (PySpark/Spark SQL), enable Power BI datasets, implement CI/CD and IaC, ensure data governance/quality with Purview, support cloud migrations and production operations while collaborating with stakeholders and agile teams.

Design and implement scalable data models and ETL pipelines (batch and streaming), ensure data quality/SSOT, collaborate with product and platform teams to resolve issues, contribute to data governance, and explore practical integrations between data engineering and AI.

The role involves operational support for data warehouse systems, optimizing pipelines on AWS, managing CI/CD processes, and collaborating on data transformations.

Design and maintain data architecture and pipelines to support compliance and risk teams. Build and optimize data models, standardize metrics, and create data dictionaries. Implement data quality, lineage monitoring, AI-driven agents for false-positive reduction and automation, and participate in on-call rotations to ensure SLAs are met.

As a Sr. Lead Data Engineer, you'll collaborate across teams to develop technical solutions, lead developers, and utilize big data technologies and cloud services to support data transformations.

Own and operate the iMData platform: design and build Databricks-based ETL pipelines using PySpark and medallion architecture, create gold-layer star schemas, migrate assets from Synapse to Databricks, implement CI/CD and Terraform IaC, ensure data security and observability, mentor junior engineers, and collaborate with stakeholders and ML engineers to deliver production-grade analytics and AI-ready data.

Lead design and delivery of scalable, secure cloud data pipelines and products. Translate requirements into architecture, apply advanced data modeling (Data Vault 2.0/dimensional), embed data quality, observability, security, and DataOps/CI-CD practices, optimize performance and cost, mentor engineers, and enable AI/ML-ready datasets within an agile DevSecOps model.

Design, build, and operate scalable cloud data pipelines and platforms (Azure preferred). Implement DevSecOps, CI/CD, automated testing, monitoring, performance tuning, and production readiness. Mentor engineers, drive operational excellence, and translate requirements into robust technical designs. Apply healthcare domain knowledge and collaborate in agile teams to deliver secure, reliable data products.

Design, build, operate, and support ETL/ELT pipelines, integrations, and curated datasets across enterprise systems (Salesforce, Deltek, Autodesk, Azure, Microsoft Fabric). Implement data models, orchestration, API-first services, data quality, governance, and monitoring to support BI, reporting, AI/ML, and secure data delivery.

The Data Engineer III designs and implements data pipelines and storage solutions, ensuring data quality for enterprise decision-making and collaboration with various teams to enhance data governance and architecture.

As a Data Engineer, you will optimize data pipelines, develop code in Python and Spark, manage cloud infrastructure, and drive data solutions.

The role involves migrating on-premises databases to AWS, developing Python scripts for data processing, and building AWS data pipelines. Responsibilities include supporting application teams, data modeling, and ensuring system efficiency.

Design, build, and automate scalable data platforms (lakehouses/warehouses). Implement and optimize ETL/ELT pipelines using Databricks and dbt, apply Medallion Architecture, manage IaC/CI-CD, ensure data security and governance, and integrate pipelines with BI tools while engaging with stakeholders.

Design, build, and optimize scalable Azure data platforms and lakehouse architectures. Develop ETL/ELT pipelines (PySpark, ADF, Fabric), enforce data governance and quality, enable Power BI reporting, lead cloud migration and CI/CD, and provide production support and performance tuning across enterprise data systems.

Build and maintain Databricks data pipelines ingesting Snowflake and data lake sources, implement medallion architecture transformations, ensure pipeline health and monitoring, create curated datasets for analytics and ML, and partner with data scientists and stakeholders.

Senior individual contributor who designs, builds, and evolves Azure-based enterprise cloud data platform capabilities. Guides architecture, standards, reusable components, automation, security, and enablement for analytics, ingestion, storage, processing, and operationalization while providing hands-on technical leadership and mentorship.

Lead design, build, troubleshoot, and deliver enterprise-scale data solutions on Azure and Hadoop. Provide technical oversight, mentoring, enforce standards, code, unit test, and collaborate with cross-functional partners to implement scalable data pipelines and analytics platforms.

Design, build, test, and operationalize data pipelines and solutions using Databricks and SQL. Ensure data quality, governance, and stakeholder collaboration to enable BI and AI/ML analytics; troubleshoot, document, and support data products.

Design, build, and support enterprise data integrations, pipelines, and analytics-ready data products. Extract, transform, validate, and deliver data securely and reliably using cloud analytics platforms, CDC tools, API integrations, and BI artifacts to support operational reporting and decision-making.

Design, build, and maintain cloud-based ELT data pipelines and analytics-ready datasets using Snowflake, dbt, and integration tools (Fivetran/Airbyte). Implement CDC and incremental loading, optimize Snowflake performance, enforce data quality and monitoring, create dimensional models for reporting, enable CI/CD for dbt projects, and collaborate with analytics and stakeholder teams to support reporting and advanced analytics.

As a Senior Data Engineer, you'll design and build data solutions, optimize data pipelines, and ensure data governance while mentoring team members.

As a Senior Data Engineer, you'll design and build data pipelines and architectures, ensuring data quality and governance while mentoring peers.