Top Data & Analytics Jobs

As a Senior Data Engineer, you will build complex data solutions and pipelines, support analytics growth, and educate users. Collaboration and advanced technical skills are essential.

The Senior Data Engineer designs, builds, and maintains data pipelines and ensures data quality controls while supporting data analytics and reporting needs.

Lead architecture and hands-on engineering to design, scale, and govern a cloud-native lakehouse using Databricks and Microsoft Fabric. Build batch/streaming pipelines, ensure HIPAA-compliant PHI handling, produce analytics-ready datasets, mentor engineers, and drive platform strategy, governance, and reliability.

The Data Platform Engineer will support Corporate Data Science and Analytics teams by curating datasets, optimizing code, and building ETL flows for data products. Responsibilities include managing production services and using cloud technologies.

The role involves designing and managing data pipelines, developing canonical datasets, and ensuring data integration and compliance. Collaborate across teams to meet data needs and maintain data architecture.

The Senior Data Engineer will design, develop, and maintain data platforms, create ETL processes, handle data quality issues, and mentor teammates while ensuring scalability and performance in data solutions.

Design, build, and own data infrastructure and ETL/ELT pipelines (Airflow, S3, Lambda) into a governed Snowflake warehouse. Implement data quality, IaC (Terraform/CDK), CI/CD, and analytics solutions (SQL, Tableau). Enable ML/LLM use cases like forecasting and anomaly detection and deliver automated reporting and data-driven marketing outputs.

Design, build, and maintain scalable data pipelines and tenant-aware APIs to ingest and transform data from varied sources. Work with event-driven and batch architectures, implement authentication and integration patterns, ensure observability/monitoring, optimize data flows for cost and performance, and collaborate with product, infrastructure, and engineering teams to onboard and maintain data sources at scale.

Partner with stakeholders to define metrics and deliver dashboards and insights. Build and optimize data models in Amazon Redshift, design and maintain scalable ETL pipelines using Python and Apache Airflow, monitor data quality and pipeline performance, and participate in code reviews and engineering best practices to support analytics and reporting needs.

Lead architecture and implementation of an AWS-native data platform powering analytics, ML, and AI workflows. Build scalable ETL/ELT pipelines (Airflow, Fivetran, dbt), enforce governance, observability (Datadog), and data quality, and provide technical leadership across Data Science, Analytics, Product, and Engineering.

Design and build scalable cloud data pipelines for high-volume manufacturing and IoT data. Bridge OT/IT systems for real-time extraction using industrial protocols, implement medallion/lakehouse architectures on Databricks/Snowflake/AWS/Azure, and apply analytics and lean methodologies to improve yield, uptime, and efficiency.

Senior Data Engineer responsible for designing, building, and maintaining scalable data pipelines, integrations, and data warehouses. Collaborate with architects, data science, and business teams to transform and prepare data for analytics and ML, ensure data quality, governance, HIPAA compliance, and mentor junior engineers.

Build and maintain scalable ETL pipelines using Python, Spark, and Airflow; collaborate with AI/ML and Product teams to deliver AI-native data products; identify and resolve ETL bottlenecks; ensure code quality through reviews and tests; own sprint deliverables and contribute to roadmap planning and major epics.

Lead engineering strategy and hands-on implementation for Finance & Actuarial data platforms. Architect no-touch automated data pipelines, drive cloud migrations (Azure Synapse/Databricks/Snowflake), embed AI-assisted development and modern DevOps, establish CI/CD and runbooks, resolve complex incidents, evaluate tooling, and mentor engineering squads while communicating strategy to executive stakeholders.

Triage and resolve Master Data Management (Party, Risk, Reference) issues in Stibo STEP, run targeted data-cleansing sprints, monitor data quality dashboards, support releases/UAT, and maintain documentation and playbooks to prevent recurring data issues.

Design and implement scalable AWS-based data infrastructure using Spark and Scala. Build fault-tolerant batch and streaming pipelines, optimize storage formats and engines, collaborate with Data Science and Product, implement automated data quality checks, and deliver performant data assets and APIs.

Design and implement scalable data infrastructure in AWS using Spark and Scala. Evolve core data pipelines, store data in optimal engines/formats, build knowledge graphs and APIs, optimize AWS resources, implement automated data quality checks, and collaborate with Data Science and Product teams to deliver reliable, large-scale data services.

Lead design and operation of identity resolution and data governance systems. Build batch and streaming pipelines, APIs, and tooling for identity ingestion, matching, lineage, quality, access controls, and privacy compliance (GDPR/CCPA). Collaborate with product, analytics, legal, and security to ensure privacy-by-design, monitoring, and documented runbooks.

Lead design and implementation of identity resolution and data governance systems. Build batch and streaming pipelines, APIs, and services to ingest, normalize, link, and version identity data. Ensure auditable matching, data lineage, quality checks, schema enforcement, access controls, and privacy-by-design. Collaborate cross-functionally with product, analytics, legal, privacy, and security teams and create documentation, monitoring, and runbooks.

Design and implement scalable data infrastructure and pipelines on AWS using Spark and Scala. Build fault-tolerant batch and streaming workflows, optimize storage formats and engines, enforce automated data quality checks, and collaborate with Data Science and Product teams to deliver reliable data assets and APIs.

Design, build, and optimize scalable data infrastructure and pipelines on AWS using Spark/Scala. Store and model data in appropriate engines and formats, implement knowledge graphs accessible via batch jobs and APIs, enforce automated data quality checks, and collaborate with Data Science and Product teams to deliver performant, cost-effective data services.

Lead development of large-scale data analysis and validation workflows for autonomous driving ML. Design metrics, build datasets, run statistical error and regression analyses, collaborate with ML and software teams, and maintain AWS/Kubernetes orchestration for large-scale evaluation.

The Data Visualization Developer will create and support dashboards in Power BI, develop SQL scripts, perform regression testing, and troubleshoot existing scripts.

Seeking a Senior BODS Developer to develop and maintain complex BODS processes for data transformation. The role includes improving data quality using Information Steward and GAC/URAC techniques, collaborating with teams, creating documentation, and mentoring others.

The Lead Data Engineer at Lennar will design and implement data engineering solutions, lead the data platform team, and ensure data quality and accessibility for business insights.