Sr. Data Engineer
Build and scale core data infrastructure, pipelines, and services to power products and analytics. Design and implement a robust data warehouse and curated data sets to support operational and research use cases.
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Build and scale core data infrastructure, pipelines, and services to power products and analytics. Design and implement a robust data warehouse and curated data sets to support operational and research use cases.
Architect complex systems and make critical technical decisions while mentoring engineers and promoting engineering excellence across teams. Align technical strategies with business goals through cross-functional collaboration and contribute to technical roadmaps and strategic planning.
Lead the development of domain data products, including batch, streaming, and AI/ML feature pipelines. Partner cross-functionally to design scalable data solutions and ensure data reliability, governance, and performance.
Build and maintain data pipelines for collecting, transforming, and integrating data from various sources. Ensure efficient data enablement and reporting solutions through the deployment of scalable data products.
Design and implement scalable, domain-oriented data pipelines on AWS to support analytics and business-critical workflows. Collaborate with cross-functional teams to ensure data quality, reliability, and performance across various data domains.
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Design and implement scalable, domain-oriented data pipelines on AWS to power analytics and business-critical workflows. Collaborate with cross-functional teams to optimize data quality, reliability, and performance across various data domains.
Design, implement, and optimize modern data architectures using Big Data technologies, specifically focusing on data lakes and lakehouses. You will be responsible for collecting, cleaning, and orchestrating large volumes of structured and semi-structured data to drive business decision-making.
Design and implement scalable data pipelines and ETL/ELT processes using GCP services like Dataflow and BigQuery. Collaborate with clients to translate business needs into technical data solutions while optimizing performance and costs.
Design and maintain scalable data pipelines and analytical data models to power clinical operations and AI initiatives. Collaborate across teams to build dashboards and contribute backend application code for data-intensive features.
Lead the design and development of scalable data processing and persistence components within agile teams. Provide technical leadership, enforce development best practices, and manage the performance and career growth of junior staff.
Design and develop large-scale data processing and persistence software components within agile teams. Provide technical leadership, mentor team members, and ensure software meets non-functional requirements and operational readiness.
Develop and maintain ETL processes using Python and PySpark within Azure Synapse Analytics to ensure efficient data extraction and loading. Design and optimize data warehousing structures, including star schemas and data lakes, to enhance data management and performance.
Design and build agentic AI systems and production-grade data pipelines to power user-facing features and internal intelligence. Develop backend services primarily in TypeScript and Python to translate complex operational workflows into scalable systems.
The role involves designing and optimizing data flows within a Fabric Lakehouse environment, focusing on low-latency processing and multi-stack integration. Responsibilities include implementing data design patterns like SCD and managing transaction logs for Delta Lake.
Design and build operational data systems, including pipelines, storage layers, and APIs for real-time enforcement and customer insights. Balance streaming and batch paradigms to support both transactional identity services and analytical security posture requirements.
Design, develop, and support cloud-based data solutions with a focus on automating ETL processes using AWS Glue and Kiro. The role involves optimizing data pipelines and evolving the data platform toward decentralized architectures.
Design, develop, and maintain scalable ETL/ELT pipelines and data integration solutions using BigQuery and Python. Collaborate with Analytics and BI teams to optimize SQL queries and ensure data quality and availability.
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Lead and mentor a team of data professionals to build scalable analytics systems and ELT pipelines. Collaborate with cross-functional teams to translate business requirements into actionable data insights and visualizations.
Design and build resilient batch and real-time data pipelines to support critical products and business growth. Establish engineering foundations, best practices, and data models to enable scalability and product experimentation.
Lead the implementation of scalable infrastructure and distributed architectures to power biomedical data analysis. Bridge the gap between complex biological science and software engineering while ensuring strict compliance with European data protection standards.
The Senior Data Engineer is responsible for designing, managing, and optimizing enterprise data pipelines and database solutions across Azure, SQL Server, and Snowflake. They will build ETL/ELT processes and data warehouse solutions to enable trusted analytics and reporting for various business lines.
Design and optimize heat rejection and HVAC systems specifically for data centers, ensuring redundancy and energy efficiency. Conduct CFD analysis to optimize airflow and collaborate with electrical engineers to integrate critical infrastructure components.
Design and evolve the semantic modeling layer to serve as the single source of truth for business metrics and logic. Lead the technical strategy for data product enablement, performance scaling, and AI-augmented engineering workflows.
Design, develop, and maintain large-scale data ingestion and transformation pipelines using GCP. Collaborate with multidisciplinary teams to transform raw data into reliable analytical assets for business decision-making.
Architect and maintain scalable data platform infrastructure and optimize analytic query engines. Collaborate with data teams to implement robust data management solutions and observability frameworks.
Build and maintain high-performance data layers and petabyte-scale storage infrastructure for AI training and evaluation. Collaborate with researchers and engineers to solve networking and performance challenges for demanding AI workloads.
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Responsible for designing, creating, and optimizing cloud data processing solutions (ETL/ELT) and technical documentation. The role involves analyzing client business requirements to deliver optimal architectural solutions and managing potential risks.
Develop and own the Bronze and Silver data layers, focusing on the ingestion, transformation, and enrichment of raw healthcare data. Build scalable, automated pipelines using Snowflake and dbt to create governed and reliable data assets for business use.
Own the development of Bronze and Silver data layers, focusing on the ingestion, transformation, and enrichment of raw healthcare data. Build scalable, automated pipelines and implement dbt models to create reliable, governed data assets for business use.
As a Senior Mechanical Engineer, you will provide technical expertise and guidance to both internal teams and external clients in the data center sector. You will assist in client contact, increase mission critical work, and participate in all phases of projects from proposals to construction.
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