Senior Data Engineer
The Senior Data Engineer leads the design and optimization of complex data architectures and pipelines while ensuring data integrity. They also mentor junior team members and participate in governance and compliance meetings.
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The Senior Data Engineer leads the design and optimization of complex data architectures and pipelines while ensuring data integrity. They also mentor junior team members and participate in governance and compliance meetings.
The engineer will design, configure, and monitor production-grade ETL/ELT pipelines to ingest data into a MySQL warehouse. They are also responsible for maintaining data quality, defining integration standards, and managing API interactions across various platforms.
Design, develop, and optimize scalable data pipelines and ETL workflows using SQL, Snowflake, dbt, and Python. Collaborate with cross-functional teams to translate business requirements into robust data models and maintain data infrastructure.
You will build and maintain automated data pipelines and develop algorithms to extract relevant information from websites and images. Additionally, you will manage the data infrastructure and create analytics reports for internal and external stakeholders.
The role involves the end-to-end administration, reliability, performance, and security of PostgreSQL, Oracle, and MySQL databases across on-premises and multi-cloud environments. You will collaborate with engineering and infrastructure teams to drive cloud modernization, automation, and continuous improvement initiatives.
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You will own the full lifecycle of data products, collaborating with Data Scientists to bring real-time pricing algorithms to production. You will also architect data pipelines, manage infrastructure, and lead cross-team efforts to scale ML development and deployment.
Design, build, deploy, and maintain scalable data architectures and databases within the AWS GovCloud environment. Develop and manage data pipelines, ETL routines, and database synchronization to ensure high performance and data quality.
The role involves serving as a frontline technical expert for sensitive identity and security incidents, leading deep investigations to resolve complex customer-impacting issues. You will collaborate across global teams to restore access, validate ownership, and mentor engineers to improve support ecosystem quality.
You will architect, build, and maintain low-latency market data infrastructure, including feed handlers and distribution systems. Additionally, you will lead a high-impact team while ensuring system reliability through observability and incident response.
The role involves building and maintaining data pipelines using dbt and Airflow while developing reliable data models for analytics. Additionally, the candidate will create Power BI dashboards and translate business requirements into effective reporting solutions.
The Snowflake Data Engineer will architect, optimize, and secure cloud data environments while building and maintaining scalable data pipelines. They are responsible for automating dataset ingestion, performing data validation, and implementing best practices for Snowflake compute and storage.
You will design and implement end-to-end AI features, ranging from data pipelines to Generative AI and agentic workflows. Additionally, you will own technical workstreams, mentor junior engineers, and enforce data security and governance standards.
Design and implement modern lakehouse architectures using Delta Lake and Iceberg UniForm on GCP. Develop ingestion pipelines, data-sharing adapters, and governed access layers to support cross-functional data products.
You will build and maintain ELT pipelines while monitoring their health and data freshness within a multi-tenant environment. Additionally, you will collaborate with data and product teams to extend modeling layers and support CI/CD and ingestion projects.
You will lead the architecture and development of backend microservices that drive the distributed export ETL infrastructure. This role involves orchestrating high-throughput data pipelines and collaborating with cross-functional teams to ensure seamless data movement.
The Senior Data Engineer will design and maintain large-scale cloud data infrastructure, including efficient pipelines and microservices. They will collaborate with product owners to organize disparate data sources and optimize performance for healthcare applications.
You will lead the migration of analytics into BigQuery and build foundational ETL/ELT pipelines to consolidate fragmented data sources. You will also partner with cross-functional teams to ensure data reliability, observability, and accessibility across the organization.
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You will lead complex initiatives from system design to deployment while building scalable data infrastructure and tooling. Additionally, you will provide technical guidance to engineering and research staff to foster growth and improve productivity.
The Principal Engineer will lead the architecture, strategy, and governance of a unified, multi-cloud data ingestion platform and federated data lake. They will drive enterprise-wide technical standards, infrastructure automation, and cost-optimization initiatives to support observability, security, and AI/ML workloads.
Design, build, and scale an enterprise-grade data and AI platform to support analytics, machine learning, and Generative AI initiatives. Collaborate with cross-functional teams to develop AI-ready data products, streaming pipelines, and intelligent retrieval capabilities.
The Data Engineer will design, develop, and maintain scalable data warehouse solutions and migrate data from various ERP platforms into NetSuite. They are responsible for building reliable data pipelines, optimizing cloud infrastructure, and ensuring data quality and security.
You will design and build scalable data pipelines for multimodal agent training, including collection, curation, and quality assurance. You will also collaborate with research scientists to develop evaluation datasets and maintain infrastructure for efficient data loading and storage.
The Senior Data Engineer will design and implement end-to-end AI features, including data pipelines, GenAI workflows, and production deployments. They will also optimize scalable data systems, enforce security governance, and mentor junior team members.
Design, develop, and maintain data engineering solutions using Python and Azure services while building scalable pipelines for data processing. Collaborate with multidisciplinary teams to develop business-oriented solutions and integrate internal and external systems via APIs.
You will build AI-driven products such as agents, chatbots, and automated data systems to enhance the company's educational platform. You will also collaborate with Data Platform and Analytics Engineering teams to ensure system reliability and performance in production.
You will design and build consumable data assets on an AWS data platform while collaborating with product engineering teams to define data ownership and contracts. Additionally, you will onboard data from legacy warehouses and develop tooling to accelerate platform adoption.
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You will own and improve monitoring, observability, and engineering standards across the data platform to ensure reliable pipeline health. Additionally, you will build internal tooling and support AI adoption to remove friction for data analysts and engineers.
You will design and build Big Data, Analytics, and AI platforms while managing data pipelines and cloud infrastructure. Additionally, you will lead engineering projects, mentor team members, and provide expert consulting to clients regarding technology stacks.
You will own the end-to-end technical and operational lifecycle of client migrations, from legacy system analysis to production deployment. This involves orchestrating cross-functional collaboration and building scalable, automated migration pipelines.
You will architect and lead the MLOps and forecasting platform, bridging the gap between advanced data science and production-grade engineering. You will also oversee the design of automated pipelines and mentor senior and staff engineers to ensure operational excellence.
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