Top Senior Data Engineer Jobs

The Principal Data Engineer will lead the design and development of scalable data platforms, optimize data pipelines, and collaborate with multiple teams to enhance data solutions.

The role involves designing and managing data pipelines, developing canonical datasets, and ensuring data integration and compliance. Collaborate across teams to meet data needs and maintain data architecture.

Lead large-scale migration of document-heavy legacy systems into cloud, convert unstructured documents to analytics-ready data, build MuleSoft integrations and APIs, apply DataWeave transformations, ensure data quality, lineage, governance, and support Salesforce Data 360 implementation and cutover in Agile teams.

The Senior Data Engineer will design and operate the data platform, build ELT/ETL pipelines, optimize data performance, and ensure data quality while collaborating with business teams.

The Sr System Analyst, Data Activation Engineer designs and builds data integration pipelines, ensuring data integrity and validating data contracts for analytics platforms. This collaborative role requires functional and technical interface design, monitoring pipelines, and documenting processes to deliver reliable data.

Designs and executes full lifecycle SAP data migrations into S/4HANA including extraction, transformation, validation, reconciliation, and cutover. Partners with functional teams and infrastructure stakeholders, troubleshoots issues, documents processes, and ensures data governance and accuracy across enterprise landscapes.

Design, build, and maintain enterprise-grade data platforms and scalable ETL/ELT pipelines. Architect cloud-native data solutions, support batch and streaming processing, optimize databases, and collaborate with data scientists and engineers to enable analytics and ML initiatives.

Design, build, and operate large-scale Hadoop-based data pipelines and analytics platforms. Ingest, transform, and analyze structured and unstructured data to support analytics, ML, and reporting. Ensure reliability, performance, and cost-effectiveness in production, and troubleshoot, document, and optimize data workflows.

Design, build, and optimize ETL pipelines and data infrastructure on AWS (EMR, S3, DynamoDB). Collaborate with data science on entity resolution and data products, implement orchestration with Airflow, write/tests PySpark jobs, ensure data quality/governance, and produce analytics and documentation.

Design, build, and maintain enterprise data warehouses and lakes; implement ETL pipelines; optimize data models and performance; produce analytics and predictive models; create dashboards and visualizations; monitor data quality; document and collaborate with stakeholders to drive data-driven business solutions.

Design, build, and optimize scalable data pipelines and models using Snowflake, SQL, Python, Kafka, dbt, and Argo. Support near-real-time integrations, CI/CD workflows, data quality, and performance; mentor engineers; partner with product and analysts to deliver production-ready, AI-enabled data solutions.

Design, build, and optimize scalable data pipelines and systems; ensure data quality, performance, and reliability; collaborate with stakeholders; lead small projects; mentor junior engineers; enforce data engineering best practices and support cloud-based data platform solutions.

Lead ownership of database performance and ETL pipelines: build and monitor data movement from AWS PostgreSQL into Snowflake, audit and tune SQL, maintain DB health/security, and troubleshoot production performance for high-volume messaging services.

Lead design and delivery of production data platforms, pipelines, and analytics. Architect Snowflake/Databricks solutions, build ETL/streaming ingestion, implement dbt transformations, data quality, observability, and governance, support BI and AI/ML feature/data pipelines, and mentor engineers while driving DataOps and platform best practices.

Design, build, and maintain data warehouses and ETL pipelines using Azure SQL and Azure Data Factory. Collaborate with analytics and business partners to define requirements, improve data quality/governance, run migrations from on-prem SQL, optimize stored procedures and replication, support CI/CD for multiple environments, and document work in Jira.

Design, build, and maintain scalable ETL/ELT data pipelines and analytical platforms on AWS and Databricks. Migrate legacy workflows to cloud-native services, implement data lake and catalog solutions, enable AI/RAG/vector search, ensure FedRAMP/NIST compliance, optimize performance, and mentor junior engineers while collaborating in Agile teams.

Build, own, and monitor end-to-end data pipelines using Snowflake, Airflow, Fivetran, and DBT. Write advanced SQL and Python for ETL, model raw data into marts, enforce data quality checks, diagnose and fix deep data issues, and optimize database performance.

Design, build, and operate large-scale Hadoop-based data pipelines and analytics platforms. Ingest, transform, and analyze structured and unstructured data to support analytics, machine learning, and reporting. Ensure reliability, performance, and cost-effective production deployments.

Lead design and delivery of the enterprise Data Platform including data lake, analytics, and certified data products. Architect solutions, automate pipelines, implement monitoring, mentor engineers, translate business needs into technical architectures, and document systems for sustainability.

Design, develop, and execute data migration solutions for Dynamics CRM/365 using KingswaySoft and SSIS. Build SQL queries, stored procedures, and SSIS packages; perform ETL, data mapping, cleansing, validation, testing, and production deployments. Migrate structured and unstructured data (attachments, correspondence), troubleshoot integration issues, and produce technical migration documentation while collaborating with senior developers and business analysts.

Design, develop, and execute enterprise CRM data migrations into Microsoft Dynamics CRM/365 using KingswaySoft and SSIS. Extract, transform, cleanse, validate, and load structured and unstructured data from legacy systems, optimize SQL/SSIS, troubleshoot performance, support integrations and customizations, perform validation testing and production cutovers, and document migration architecture and procedures while ensuring data governance and security compliance.

Lead data migration and ETL development for an SAP BRIM implementation: analyze legacy sources, design/execute EMIGALL and BODS migration jobs, validate/reconcile data, support integration with S/4HANA and CRM, and provide testing, production support, documentation, and stakeholder collaboration.

Design, build, and operate Alpaca's scalable data platform and lakehouse infrastructure. Build low-latency streaming and CDC ingestion, batch pipelines landing in Iceberg, and tooling for BI and AI consumers. Manage IaC, Kubernetes deployments, monitoring/incident response, and partner with DevOps and analytics teams to meet growing data requirements.

Design, build, and scale streaming and batch data pipelines, embedding workflows, and vector store integrations to support AI applications. Implement AI-optimized data models, ensure observability and data quality, and collaborate across infra, ML, and product teams while mentoring engineers and delivering production-ready, reliable data foundations.

The Senior Data Engineer designs scalable data solutions to harmonize data across various ERP systems, implementing ETL/ELT pipelines and ensuring data quality and governance.