Top Data & Analytics Jobs

Design, build, and operate scalable data pipelines and systems; own data architecture, data quality, SLAs, query performance, and reusable tooling; collaborate with engineering, AI, data science, and product teams; mentor engineers and promote observability and testing best practices.

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.

Design, implement, and maintain cloud-based data pipelines and platforms. Advise clients on best practices, partner with stakeholders to translate requirements, provide technical leadership and mentoring, and stay current with cloud data technologies and architectures.

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.

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.

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.

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.

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.

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.

Analyze existing systems, design cloud-ready data processing workflows, develop specifications and migration tools, validate implementations via automated testing, and report progress. Collaborate with stakeholders and developers to optimize BI/reporting solutions and complete relevant technical training.

Design and build data infrastructure and data pipelines, focusing on big data processing, modeling, and automation to support engineering teams at NextSense.

Design, build, and optimize scalable ETL/ELT pipelines and cloud data platforms. Integrate data from SQL Server, Yardi, Salesforce and APIs into AWS (S3, Redshift). Collaborate with analytics, data science, and business teams to deliver trusted datasets, ensure data quality and governance, and implement DevOps, CI/CD, and infrastructure automation for operational excellence.

Design, build, and operate Brex's data enablement platform (warehouse, streaming, replication, orchestration, observability, governance). Partner with product, data science, and analytics teams to deliver data-backed products, improve data competency, and maintain resilient, on-call data architectures.

As an Associate Engineer in Data Science, you will leverage data analysis and machine learning to solve complex problems and develop inspiring digital products.

Nagarro seeks an Associate Principal Engineer in Big Data to leverage extensive IT experience for strategic organizational value. The role values self-starters and innovation.

Own ingestion, transformation, validation, and normalization of clinical and EHR data pipelines (HL7 v2, FHIR, CDC) into performant Snowflake and MySQL schemas. Build and monitor AWS-based pipelines, ensure data quality and PHI-compliant handling, and support downstream ML and application needs across enterprise integrations.