Top Senior Data Engineer Jobs

Design, build, and tune scalable data pipelines and streaming platforms using open-source tools (Kafka, NiFi, Hive, MapReduce) and NoSQL/SQL datastores. Automate ingestion, transformation, and augmentation of structured and unstructured data, collaborate with analysts, developers and data scientists, and ensure high availability and performance for analytics and transactional systems.

Design, develop, debug and tune Hadoop-based ETL using HDFS, Pig, Hive, HBase, Sqoop and Java. Provide technical oversight to the Hadoop team, write/modify shell or Python scripts, liaise with application teams, perform performance tuning and troubleshooting, and provide on-call weekend support.

Design, develop, and support Big Data solutions on Teradata Aster and Hadoop platforms. Build ETL pipelines, data mining, reporting, and predictive analytics; write efficient code for large/unstructured datasets; translate business use cases to production; mentor users; contribute to Big Data roadmap and standards.

Build a greenfield data platform and ingestion pipelines for payments, marketing, and operational data across AWS and GCP; implement a Lakehouse with medallion-layer transformations in dbt/SQLMesh (Redshift/BigQuery); own orchestration (Dagster/Airflow), lineage, backfills, retries, alerting; apply IaC with Terraform and cost controls; operate autonomously in a remote, async environment.

Design, build, test, and maintain ETL pipelines, data warehouse and BI solutions. Partner with business users, perform performance/regression testing, review code, troubleshoot data issues, and oversee production deployments.

Operate and ensure reliability of ELT/data and integration pipelines (Airflow, Azure Integration Services). Monitor SLAs, respond to incidents, perform root cause analysis, manage Snowflake RBAC, support deployments (dbt, GitHub Actions), optimize performance, and collaborate across engineering, security, and analytics teams to maintain secure, on-time data delivery.

Lead design and implementation of scalable data architectures in Azure/Databricks/Fabric, enhance governance (Unity Catalog), improve data quality frameworks, build resilient ingestion/transformation pipelines, modernize CI/CD and source control, support production and analytics/AI use cases, and collaborate with stakeholders to move proofs-of-concept to enterprise solutions.

Design, build, and maintain scalable Azure-based data pipelines, lakes, and warehouses. Create ETL/ELT processes, dimensional models, and business-ready datasets. Support reporting and Power BI, implement data quality, governance, monitoring, and document platform architecture and processes while partnering with stakeholders.

Lead the development and operation of a data lake for cyber operations, design schemas and indexes, build and evolve ETL pipelines, mentor engineers, and drive technical initiatives.

The role involves leading the development of data lakes, designing schemas, building ETL pipelines, and mentoring engineers while ensuring data quality and performance.

The Sr. ETL Informatica Systems Engineer develops ETL applications for the EDW/BI program using Informatica tools, managing complex SQL and APIs.

The Senior Data Engineer will design and build scalable data platforms, handle automation for data operations, and ensure reliability and performance of data pipelines while collaborating with various teams.

Build and scale Allocate's AWS-based data lakehouse and pipelines (batch and real-time). Model financial entities and integrate internal/third-party sources. Enable ML/AI workflows, vector and knowledge-graph integrations, CI/CD and containerized deployments, and collaborate with engineering to deliver reliable, production-grade data and AI infrastructure.

Lead architecture and implementation of enterprise-scale, production data pipelines and ecosystems for global, customer-facing products. Collaborate with product and engineering leadership, mentor peers, enforce code and CI/CD standards, and optimize data storage and performance for high-availability, defense-focused monitoring solutions.

Design, build, and own core data models, pipelines, and infrastructure for the Eclipse Platform and Data Marketplace. Implement data quality monitoring, collaborate on governance, build dashboards, support leadership reporting, and deliver analytics and ML/NLP solutions.

Lead a team to design, build, and maintain cloud data engineering solutions using Microsoft Fabric and Azure Synapse. Responsibilities include architecture, data pipelines, lakehouse and warehousing implementation, governance, performance optimization, mentoring engineers, cross-functional collaboration, support/on-call, documentation, and ensuring reliability and compliance.

Design, build, and maintain scalable end-to-end data pipelines and enterprise data platform components (Snowflake/Python/dbt). Lead architecture, mentor engineers, implement CI/CD, automated testing, and collaborate with stakeholders to deliver healthcare-focused data solutions (payer claims, attribution).

Design, build, and operate scalable AWS and Snowflake data pipelines and data products to support reporting, analytics, machine learning, and operational decision-making. Develop curated datasets, data models, and complex transformations; troubleshoot distributed systems; ensure security, testing, and reliability; and partner with business stakeholders across Disney Parks in an Agile environment.

Own and harden Plot's core data platform: stabilize high-throughput ingestion, design read-optimized schemas and partitioning, separate transactional vs analytical workloads, ensure performant data access for dashboards and AI agents, write RFCs, and raise reliability and observability across teams.

Design, build and maintain a self-service data platform to enable teams to create data products. Support real-time analytics, batch processing and ML workloads. Implement secure, scalable, compliant infrastructure with IaC and automation. Enable ingestion, processing and consumption of data at scale. Mentor teammates and drive engineering excellence.

Design, build, and maintain scalable data models, ETL/streaming pipelines, and cloud-native data platforms. Ensure data quality, governance, performance tuning, and enable ML workflows. Lead cross-functional teams, mentor engineers, and implement CI/CD, monitoring, and cost-optimized solutions to support analytics and real-time inference.

Build, operate, and modernize scalable data pipelines and warehouse environments for lottery reporting, analytics, and AI readiness. Improve ingestion, transformations, data models, contracts, observability, lineage, and onboarding patterns. Automate operations, troubleshoot production issues, mentor engineers, and support migration from legacy to cloud architectures while ensuring data quality, reliability, and regulatory continuity.

The Staff Data Engineer will lead financial data operations, ensuring accuracy and reliability of data pipelines, while collaborating with Finance, Product, and Engineering teams to enhance systems and decision-making processes.

The Senior Data Engineer designs and optimizes data pipelines for marketing analytics, ensuring data accuracy and collaborating with teams to meet reporting needs.

The Senior Data Engineer will design, build, and optimize data pipelines and models, lead a team, and work with stakeholders to deliver data-driven solutions for a Federal client.