Top Data & Analytics Jobs

Design, build, and maintain scalable cloud data pipelines and warehousing/lake solutions. Advise customers on best practices, lead technical design, mentor engineers, and collaborate with stakeholders to deliver supportable data engineering solutions across cloud platforms.

Lead design and delivery of cloud data pipelines and architectures, advise clients on best practices, implement ETL/orchestration, work with product owners to meet requirements, provide technical leadership and mentor engineers, and maintain scalable data warehouse and lake solutions across cloud platforms.

Lead design and implementation of cloud-based data pipelines and distributed data systems. Advise clients on best practices, partner with stakeholders to translate requirements, provide technical leadership and mentorship, and maintain scalable ETL, warehousing, and streaming solutions across cloud platforms.

Lead design and implementation of cloud-based data pipelines and architectures. Advise clients on best practices, build/operate distributed ingestion and processing systems, mentor engineers, and collaborate with stakeholders to deliver scalable data warehousing and lake solutions using modern cloud technologies.

Serve as a trusted advisor designing, implementing, and maintaining cloud data pipelines and systems. Partner with product owners and SMEs to translate requirements, provide technical leadership, mentor engineers, and ensure scalable, supportable data solutions using modern cloud and ETL technologies.

Design, implement, and maintain cloud-based data pipelines and warehousing/lake solutions. Advise clients on best practices, lead technical decisions, mentor engineers, and collaborate with stakeholders to deliver scalable, maintainable data engineering solutions.

Design, implement, and maintain cloud-based data pipelines and platforms. Advise clients on best practices, integrate disparate data sources, optimize data warehousing/lake solutions, mentor engineers, and ensure scalable, maintainable data architectures across cloud environments.

Support design and implementation of data visualization, reporting, and ETL solutions in an Azure data lake/warehouse environment. Build data pipelines, develop scalable data assets, design logical and physical data models, retrieve and analyze data with SQL, and create Power BI/Tableau/Qlik visualizations. Participate in Agile delivery, data profiling, and data governance while collaborating with business stakeholders to translate requirements into analytics solutions.

Design, build, and operate large-scale Hadoop-based data pipelines and analytics platforms. Ingest, transform, and analyze structured and unstructured data to support enterprise analytics, ML, and reporting. Ensure reliability, performance, and cost-effectiveness in production, and troubleshoot, document, and optimize data workflows.

Own the 2-3 year architecture and reliability of high-volume catalog, pricing, and inventory ingestion. Lead migrations from legacy batch to modern systems, define data SLAs, build observability and orchestration, mentor senior engineers, and resolve cross-team, high-severity data problems.

Designs, builds, and deploys data pipelines and integrations to support analytics and machine learning for digital pathology. Partners with product owners and ML teams to extract, transform, validate, and visualize data, enabling insights and model development. Maintains platform knowledge and provides consultative support across teams.

Design, build, and maintain scalable batch and streaming data pipelines, improve data modeling and governance, contribute to enterprise data architecture, and collaborate with cross-functional teams to ensure reliable, high-quality data for analytics and operational use.

Design, build, and maintain scalable AWS-based data architecture and pipelines. Manage Redshift models and schemas, ensure data quality and observability, automate ETL/ELT using Glue, Lambda, dbt and other tools, collaborate with Data Science and Analytics, document pipelines, and mentor peers to support reliable self-service analytics.

Lead teams to design, build, and operate scalable, AI-ready data pipelines and ecommerce data products (especially Shopify). Build semantic layers, curated data marts, and data models; ensure data quality, monitoring, and performance. Collaborate with data scientists, analysts, and governance to support feature engineering, ML datasets, and reliable downstream consumption.

Build and own Plug's governed data layer: dbt transformation models and MetricFlow definitions, ingestion pipelines (Fivetran, HubSpot, OEM APIs), ML feature store maintenance, data quality monitoring, and support self-service reporting. Collaborate with engineering and ML teams, participate in incident response, and raise data engineering standards.

Lead design and evolution of a company-wide data platform spanning streaming, batch, warehousing, orchestration, governance, and ML enablement. Deliver core platform capabilities, reliable real-time pipelines, shared tooling, and scalable infrastructure. Drive cross-team initiatives, champion golden paths, improve reliability/cost/observability, ensure regulatory compliance, and mentor senior engineers while influencing technical strategy and standards.

Design and build a scalable cloud data platform on Google Cloud, create reliable batch and streaming ETL/ELT pipelines, enforce data quality and observability, automate IaC/CI-CD, and support analytics, ML, and product teams with high-quality data.

Build and scale optimized data pipelines and data engine architecture to run ML models, reduce annotation costs, integrate foundation models for labeling and QA, use software/hardware-in-the-loop testing, and collaborate with DoD customers to understand requirements and support field events.

Own design, build, and reliability of a cloud-native data lakehouse (Bronze->Silver->Gold). Build scalable ETL/ELT pipelines (ADF, Airflow), optimise Snowflake, develop dbt models, embed data quality/observability (Elementary), manage ADLS Gen2 and Azure serverless components, and drive infra-as-code, CI/CD, and cross-team collaboration.

The Senior Data Engineer will build and maintain data pipelines, distributed ETL/ELT workflows, and data storage systems while collaborating with various teams to optimize data quality and performance.

Design, build, and optimize large-scale data pipelines, ETL processes, data models, and data warehousing solutions. Manage and tune databases (SQL and NoSQL), lead big data and cloud implementations (Snowflake, Fivetran, dbt, Airflow), apply DevOps and containerization for data workflows, and mentor junior engineers to deliver scalable data processing and actionable insights.

The Data and Analytics Engineer will build and maintain scalable ELT pipelines, leveraging data for analytics and reporting within the Snowflake data architecture.

Design, build, and optimize high-throughput data pipelines and infrastructure for Defense Health. Develop RESTful APIs and cloud data solutions (AWS), apply DevSecOps and TDD, use Python, Trino, Spark, dbt, and Rancher Kubernetes, and collaborate with stakeholders to deliver secure, production-grade analytics services.

Lead design, build, and maintain scalable data pipelines and infrastructure. Collaborate with analysts and data scientists, ensure data quality, optimize performance, troubleshoot issues, document architecture, and mentor junior engineers.

As a Data Engineering Architect, lead the transformation of data engineering into a modern platform, oversee architecture and technical leadership, design scalable systems, ensure data quality and governance, and mentor teams for a data-driven culture.