Top Data Engineer Jobs

Design, build, and optimize scalable batch and streaming data pipelines. Model and process structured and unstructured data, ensure production reliability and observability, apply ML techniques for insight extraction, and drive data strategy while adopting modern tooling and IaC practices.

Lead design, build, optimization, and operation of scalable Databricks-based batch and streaming data pipelines for healthcare programs. Ensure DataOps, data quality, lineage, observability, CI/CD, and compliance with CMS and federal healthcare regulations. Collaborate with architects, data scientists, and stakeholders, troubleshoot production issues, and mentor junior engineers.

Design, build, and optimize scalable end-to-end data pipelines and Snowflake data warehouses. Develop BI solutions (Power BI/Tableau/Cognos), enforce data quality/governance, integrate investment data vendors, collaborate with stakeholders, mentor junior engineers, and follow SDLC/DevOps best practices.

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.

Develop, debug, and optimize Hadoop-based data solutions using Pig, Hive, Sqoop, HBase and Java. Write and maintain shell/Python scripts, perform performance tuning, apply Big Data architecture/design patterns, guide the Hadoop team, coordinate with application teams for issue resolution, and provide on-call weekend support.

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, 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.

Develop and maintain Big Data applications using Java/Spring and Python on MapR HDFS with MapReduce, Pig, and Hive. Design NoSQL data models in HBase, participate in SDLC activities, configuration management, code reviews, and collaborate with offshore teams. Apply credit risk/fraud/payments domain knowledge and use tools like Jira, Maven, and SOAP UI.

Own and evolve the data platform: architect, build, and maintain data models, pipelines, and access layers. Ensure data quality, governance, and reliability; monitor and optimize infrastructure; provide technical leadership, code reviews, and collaborate with cross-functional teams to deliver scalable data solutions for operations and analytics.

As a Senior Data Engineer, you will design and maintain data systems for Aircapture, focusing on building data pipelines and making architectural decisions to support climate technology.

In this role, the Senior Data Engineer designs and implements data architecture for analytics and ML initiatives, develops ETL/ELT pipelines, and ensures data quality and compliance, while mentoring junior team members.

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

Lead design, build, and maintain complex ETL/ELT data pipelines and integration solutions to support analytics and reporting. Ensure data quality, optimize processing for performance and scalability, monitor pipelines, document data lineage and procedures, and collaborate with stakeholders and analysts to resolve data issues and requirements.

Build and maintain scalable data pipelines and Python automations for ingesting, processing, and enriching data. Integrate SaaS sources via APIs, use Databricks/PySpark/Delta Lake and AI tools to power lead generation, enrichment, deduplication, and entity resolution. Collaborate cross-functionally to translate business needs into automated, production-ready solutions.

This role involves leading data strategy and managing a team to build and maintain multimodal datasets, ensuring data quality and pipeline efficiency.

Design, build, and optimize end-to-end data pipelines and ETL/ELT processes, enforce data governance and lineage, create enterprise datasets and data models, mentor team members, and implement CI/CD for data deployments to support analytics and advanced analytics use cases.

Design and build SOCOTEC's enterprise data platform: scalable Databricks/Spark/Delta Lake pipelines, data models, and MDM. Ingest from ERP/CRM, enable batch and near-real-time processing, ensure data governance, quality, lineage, and provide datasets for analytics and AI while driving architecture and observability.

Design, build, and maintain production-grade data pipelines, Python services, and Databricks workloads for a large-scale financial data platform. Improve performance, reliability, observability, and data models; troubleshoot issues; participate in architecture, code review, and cross-team collaboration to deliver enterprise reporting and integrations.

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.

The Senior Data Engineer will build and deploy data pipelines, develop warehouse architectures, and design analytics solutions for the team.

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.

As a Lead Data Engineer, you'll design scalable data frameworks, develop data pipelines, implement data quality checks, and collaborate with stakeholders to enhance data solutions.

Design and own end-to-end data domains and pipelines for plant sensors, lab results, and historians. Build schemas, ensure data quality, observability, and lineage, and supply model-ready time-series and analytical datasets to ML and operations teams. Mentor junior engineers and define data contracts.

The Data Solutions Engineer will design and deliver data and analytics solutions, manage data pipelines, and support cloud platforms while collaborating with various teams to improve data accessibility and operational efficiency.