Top Data & Analytics Jobs

Design and implement scalable data solutions using Microsoft Fabric and Azure. Build and orchestrate ETL/ELT pipelines, develop Power BI reports and DAX, optimize T-SQL and KQL queries, model data for Lakehouse/warehouse architectures, integrate varied data sources with Spark/PySpark, automate processes, ensure governance and security, and troubleshoot pipeline issues.

Design, build, and operate large-scale, fault-tolerant real-time and batch data pipelines powering an ad-tech DSP. Collaborate with engineers and data scientists to define data models and SLAs, optimize performance and capacity, enforce data quality and monitoring, mentor engineers, and evaluate new data technologies to scale analytics and ML workloads.

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.

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 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.

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.

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 Data Analytics Engineer, you will build data pipelines, develop KPIs, collaborate with stakeholders, and promote data-driven decision-making.

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, build, and maintain enterprise data integration and BI solutions on Microsoft Fabric and Power Platform. Develop ETL/ELT pipelines, APIs, dashboards, and governance artifacts, while supporting data quality, monitoring, and stakeholder collaboration to deliver scalable analytics and integration 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.

Lead the vision and execution for scalable data governance and quality across Airbnb. Architect future-proof data ecosystems, define best practices and tooling, drive cross-functional policy implementation (privacy, legal, infosec), mentor senior engineers, and influence executive strategy to embed stewardship into the data product lifecycle.

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.

The Senior Data Engineer will design and manage petabyte-scale data pipelines, ensuring data quality and architecture for operational decision-making and ML training.

Lead design, implementation, and governance of an AWS Lakehouse platform using Medallion architecture. Build and optimize batch and real-time pipelines, enforce data quality and privacy (PII tokenization, Lake Formation), drive DataOps/CI-CD, support Customer 360/MDM, mentor a small team, and serve as incident commander for platform operations.

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.

The Senior Data Engineer will design and manage data pipelines for massive datasets, ensuring quality, cost management, and effective data operations. Responsibilities include overseeing data flows, monitoring data quality, and managing vendor partnerships.

The Principal Database Architect & Engineer will own the data components of complex infrastructure solutions and lead teams to deliver innovative database technology solutions, ensuring optimal performance and operational efficiency.

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.

Support and evolve the enterprise analytics platform: build and maintain cloud data pipelines (ingest, transform, curate), develop analytics-ready datasets, create Power BI reports and semantic models, apply Python and AI workflows for automation and validation, ensure data quality and governance, and partner with finance and IT to deliver trusted analytics.

The Technology Analyst will develop Big Data applications leveraging Hadoop, Java, and Python. Responsibilities include project lifecycle participation, team collaboration, and client interfacing in a global delivery environment.

The role involves building scalable ELT/ETL pipelines on GCP, utilizing SQL and Python, and managing security and infrastructure automation while ensuring real-time processing and resource provisioning.

Lead design and implementation of Databricks/Azure data solutions to ingest, store, transform, and distribute large-scale retail data. Own features through the SDLC, mentor engineers, lead cross-functional collaboration, build REST APIs on Kubernetes, execute testing, and set technical strategy with Product, Data Science, and Architecture.