Top Data & Analytics Jobs

The Senior Data Infrastructure Engineer will design and maintain ETL pipelines, develop data infrastructure, and ensure data reliability for analytics and machine learning across teams.

The Senior Data Engineer will design, implement, and manage data pipelines for real-time analytics and ML training datasets, ensuring efficient data flow and quality in a hybrid environment.

As the Distinguished Architect, you will lead the design and implementation of CloudZero's next-generation data platform, focusing on streaming architecture, data modeling, and optimizing query engines to enhance cost attribution and performance at scale.

Design and build scalable data pipelines for Investment Data Standard and knowledge graph, implementing data quality controls and collaborating with cross-functional teams.

As a Staff Data Engineer, you will design and build data pipelines, optimize data models, and collaborate with product and engineering teams to enhance data processing capabilities.

Lead the architecture and implementation of a new People Analytics platform on a modern data stack, ensuring AI readiness, governance, and security while optimizing for performance.

The Data Platform Engineer maintains and optimizes databases and data infrastructure, collaborating with various teams to ensure system reliability and performance while automating processes and supporting data pipelines.

As a Senior Data Engineer, you will develop data pipelines, architect innovative data products, and integrate AI/ML models to enhance business insights.

The Data Engineer will optimize data infrastructure, modernize SQL processes, support data governance, and mentor team members while enhancing analytics capabilities.

The Data Analyst will analyze complex datasets, lead data integration projects, evaluate power generation systems, and develop reports using SQL and visualization tools.

The Lead Data Engineer will architect and develop reporting solutions, integrate AI, analyze complex datasets, and mentor team members to enhance data-driven decision-making.

The Lead Data Engineer will manage U.S. Data Strategy capabilities, translating business objectives into cloud data solutions, while ensuring scalability and security. This includes ETL, analytics, and technical leadership in a hybrid work environment.

Design, build, and maintain scalable ETL/data pipelines across distributed systems. Ensure data quality, integrity, security, and high availability. Monitor and optimize pipeline performance, perform root cause analysis, document systems, collaborate with global teams, and participate in on-call rotations to support production data systems.

Design, develop, and implement SQL Server/T-SQL applications and complex queries. Build, review, and maintain ETL processes using SSIS/SSRS, develop stored procedures, and tune large-volume databases across development, UAT, and production environments. Work within Scrum; telecommuting permitted. No visa sponsorship.

Lead design and delivery of a cloud-based data platform: implement CDC/streaming ingestion, modeling, transformations, cross-region DB replication, observability, governance (PII, lineage, access), and enable downstream marts while mentoring engineers and driving IaC/automation-first practices.

Design, build, and operationalize scalable data pipelines and transformations on cloud platforms. Ensure data governance, quality, and security; collaborate with data science to support ML model operationalization; mentor engineers and drive architectural decisions for enterprise analytics.

Design and implement data quality checks, monitoring, and remediation across pipelines. Investigate, analyze, and remediate data issues; automate pipelines with AI-enabled tools; collaborate with engineers, analysts, and stakeholders to ensure trustworthy data for reporting and products.

Design, build, deploy, and operate scalable production data pipelines and workflows (Airflow, BigQuery, dbt). Own medium-sized platform initiatives end-to-end, ensure SLA-driven freshness, quality, and cost controls, implement monitoring and CI/CD, participate in on-call incident response, optimize warehouse performance, and collaborate with analytics, data science, product, and engineering stakeholders.

Lead extraction, mapping, cleaning, transforming, and importing complex donor and fundraising data from legacy systems into Virtuous. Use SQL and dbt to design ETL transformations, collaborate on migration strategy, work with customers and internal teams, and solve complex data structure and relationship issues to align legacy data with Virtuous CRM best practices.

Design, build, and maintain cloud-based data infrastructure and ETL/ELT pipelines (Azure, Databricks, Snowflake, Fabric). Lead cloud migrations from on-prem SQL Server, implement Medallion/Lakehouse architectures, ensure data quality and performance tuning, collaborate with analysts and data scientists, and mentor junior staff.

Design, build, and operate production data pipelines across AWS, Databricks, and Snowflake. Modernize and migrate legacy AbInitio workloads, embed data quality/observability/lineage, optimize cost/performance, drive CI/CD and DataOps practices, integrate AI coding tools, mentor engineers, and standardize reusable pipeline frameworks.

Lead QA/SDET efforts for an enterprise data and analytics platform: design and implement automated data validation and data quality frameworks across Medallion layers, integrate tests into CI/CD, perform cross-source reconciliation and UAT for BI tools, drive defect triage, and ensure lineage, auditability, and model testing from feature engineering through scoring.

Design, implement, and maintain data analytics platforms, pipelines, dashboards, and ML models for animal nutrition research. Collaborate with researchers, barn managers, and cross-functional teams to collect and analyze farm data, deliver insights and alerts, and develop digital products to improve research, productivity, and sales.

Design, build, and maintain reliable data pipelines and models using SQL, Python, and Databricks/Spark. Translate multi-source schemas into scalable data models, enforce data hygiene and privacy, add tests/documentation/lineage, and collaborate with analytics, product, marketing, and vendor teams to deliver trustworthy data for personalization and marketing.

As a Data Platform Engineer, you'll architect and implement data services, build data pipelines, optimize for real-time risk assessment, ensure data governance, and collaborate across teams.