Top Data & Analytics Jobs

Join BlackRock's Advanced Data Analytics team to deliver research and data solutions for structured products, leveraging data technologies and statistical methodologies.

The Principal Data Engineer at NBCUniversal leads the development of data applications, manages data pipelines, and collaborates with teams while coaching junior engineers. Responsibilities include designing scalable data solutions and integrating AI technologies.

Own and modernize Upsides analytics data platform: migrate pipelines, reduce cost, improve governance, design reusable modeling/orchestration patterns, deliver domain-critical data products, lead cross-functional initiatives, mentor engineers, and support ML and product teams.

Design, build, and optimize SQL and NoSQL database solutions (PostgreSQL, Elasticsearch, DynamoDB). Develop stored procedures, functions, triggers, and complex queries. Implement CDC and AWS DMS, manage platform via GitHub/CI-CD and Terraform, monitor and tune performance, participate in Level 3 on-call, and collaborate with analysts, architects, and developers to deliver scalable data services.

The Data Engineer II supports data infrastructure operations, resolves issues, ensures platform stability, and implements improvements while collaborating with engineering and analytics teams.

Entry-level Data Engineer responsible for building and maintaining cloud-based data assets and pipelines, improving data quality and automation, investigating data integrity issues, and collaborating with architects, analysts, and stakeholders. Uses SQL and Python, participates in Agile practices, leverages AI-powered developer tools for spec-driven development, and follows responsible AI and data privacy practices.

The Data Engineer II will build and maintain data pipelines and warehouses, ensure data quality, and collaborate with cross-functional teams to support business intelligence and machine learning efforts.

As a Data Engineer at PNC, you will design, build, and maintain robust OLTP databases, ensuring high availability and strong performance while collaborating with cross-functional teams to manage data integrity and security.

The Data Engineer II will maintain CI/CD pipelines, develop AI/ML platforms, process telecom data, and optimize data storage and retrieval strategies.

Build and maintain reliable data pipelines, Airflow DAGs, and Snowflake-based Data Vault/warehouse models. Implement CI/CD, automated testing, observability, and production support while partnering with stakeholders and developing insurance domain expertise.

Design, build, and maintain scalable data pipelines and API integrations; implement data quality monitoring and alerting; troubleshoot data issues; collaborate with business stakeholders; support CI/CD processes and scale architecture for future needs.

Design, build, and maintain scalable data architectures and pipelines; ensure data quality, lineage, and observability; implement solutions across cloud and on-prem platforms; provide accessible data consumption methods; collaborate cross-functionally and exercise independent technical judgment.

Design, build, and maintain data architectures and pipelines to ensure data quality, lineage, and accessibility. Implement ingestion frameworks and transformations across cloud and on-prem platforms, enable data consumption (APIs, views, extracts), monitor data observability, and collaborate cross-functionally to meet privacy and business requirements. Work may include nights/weekends and requires independent technical judgment.

The Principal Data Engineer will lead data engineering efforts on public cloud, design scalable solutions, build data pipelines, and drive deliverables with a high level of technical expertise in relevant technologies.

Develop and maintain data contracts, metadata standards, AI-readiness scoring pipelines, and governance/compliance tooling. Build quality monitoring, semantic layer assets, and AI-augmented development workflows. Collaborate with data owners and platform teams to onboard assets, ensure data trust, and enable AI-driven analytics.

The Solutions Data Engineer will manage data integrations end-to-end, utilizing FloQast's Data Platform and Data Studio to connect source systems and transform data for reliable outputs across applications.

Develop and maintain Python data pipelines and CI/CD deployments to build business data objects. Implement source-to-target mappings, unit and integration tests, and resolve complex technical issues. Follow SDLC and software product design practices, promote software quality, and collaborate across functions while working onsite in Chicago or Peoria.

Design and implement data pipelines, manage data with SQL and Python, automate workflows, ensure data integrity, and build scalable data solutions on AWS and Redshift.

Build and maintain batch ETL/ELT pipelines and Airflow orchestration using Python, SQL, and AWS. Develop operational datasets for fulfillment, inventory, shipments, and returns. Monitor and optimize pipelines, implement data quality checks and alerting, support production incident response, and collaborate with engineering, BI, and operations teams to improve pipeline scalability, observability, and reliability.

Design and implement ETL pipelines, optimize data systems, build data warehouses, and develop AI/ML models for data solutions. Collaborate with teams to deliver data-driven products and ensure data quality and governance.

As a Data Engineer, you'll lead data engineering projects, develop data transformations, build workflows with Apache Airflow, and ensure data quality and integrity while collaborating with stakeholders.

Senior Data Engineer on PwC's Managed Data, Analytics & Insights team to design, build and manage advanced data ecosystems. Responsibilities include designing data solutions and scalable pipelines, solving complex problems, mentoring junior staff, maintaining high delivery standards, and building client relationships while aligning solutions to business context.

The Data Engineer will architect ETL pipelines, manage a central data lake, and ensure data quality and best practices in collaboration with various teams.

The Senior Data Engineer will design and execute data management strategies, build cloud solutions, develop data pipelines, and ensure data quality and integrity.

The Principal Data Engineer will lead the technical strategy for data initiatives, focusing on real-time data platforms and collaboration with stakeholders to design efficient and innovative data architectures, ensuring data governance and compliance.