Top Data & Analytics Jobs

The Data Engineer II will design, build, and maintain data pipelines, ensuring data governance and security. Responsibilities include coding in Python, managing data processing, and collaborating with data teams.

Support and maintain clients' Azure data platforms and Power BI environments. Design and deploy data pipelines, models, and analytics solutions using Microsoft stack (ADF, Synapse, Databricks, SSIS/SSAS/SSRS). Troubleshoot incidents, communicate with clients, manage licensing, document environments, and promote best practices while collaborating with stakeholders and continuous skill development.

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.

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.

Design, build, and maintain Snowflake-based pipelines to produce consumer and household identity assets. Write SQL/Python to transform and deduplicate PII, investigate data quality at record level, and improve AI-assisted and rule-based matching engines. Collaborate with Data Science and engineering teams to evaluate matching performance, build evaluation tooling and dashboards, and support CI/CD, QA, and on-call production responsibilities.

The role involves designing data pipelines, developing and maintaining ETL processes, and collaborating with teams to implement data governance in a cloud environment.

Design, build, and operate secure, scalable cloud-native data platforms (lakehouse/data mesh) supporting batch, streaming, ML, GIS and operational workloads. Lead ingestion/transformation pipelines, distributed processing (Spark/Kafka), data governance, observability, and mentor teams while ensuring compliance in regulated environments.

Design, build, and operate an end-to-end data product supporting Sales across Europe. Develop and maintain Azure-based data pipelines, implement reporting layers (e.g., Power BI), ensure production readiness with monitoring and documentation, and partner with Sales, Finance, Data Scientists, and analysts to deliver reliable, scalable data solutions.

The Software Engineer will build and operate the cloud infrastructure for data ingestion, collaborating with scientists to improve dataset quality, scale, and cost efficiency for AI model training.

The role involves building data platforms and pipelines, integrating AI solutions, and collaborating with product owners to address complex client issues.

The Senior Data Engineer will design scalable data processing frameworks using Java and Apache Spark, manage data pipelines, and mentor junior engineers.

The Senior Data Engineer leads the architecture and development of the Snowflake data platform, ensuring data governance, integration, and compliance while mentoring team members and optimizing system performance.

Design and deploy scalable data infrastructure and models, maintain CDC pipelines, build reporting tools and dashboards, write high-performance SQL, partner with product and engineering to enable enterprise-wide analytics and data-driven decision making.

The Senior Data Engineer will build data pipelines and infrastructure, modernize legacy systems, and ensure data reliability for analytics at ABCorp.

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

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.

Lead data platform architecture and delivery for healthcare-focused Lakehouse/Warehouse solutions. Drive Databricks/AWS design, governance, security (PHI/PII), ETL/Delta Live Tables, APIs, modeling (FHIR/OMOP), IaC (Terraform), pipeline performance, and cross-functional collaboration to deliver scalable, production-grade data products.

The Analytics Engineer will build and maintain data models, partner on ETL pipelines, and ensure data quality for analytics. They will also work closely with business stakeholders to develop governed metrics and enable self-service analytics across the organization.

Responsible for designing, developing, and maintaining scalable data pipelines and infrastructure, implementing data governance, and collaborating with teams to meet data needs.

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

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.

Lead the technical direction of data engineering by designing ETL pipelines, ensuring data quality, optimizing infrastructure, and mentoring junior engineers.

Establish and own the data analytics foundation for a GPU marketplace: define metrics, build data pipelines and dashboards, ensure data correctness, and deliver actionable insights to leadership.

The role involves developing applications and tools for data visualization in clinical trials, managing projects, and ensuring compliance with data standards. Responsibilities include programming in R, creating dashboards, and integrating data across clinical systems.

The Sr. Data Engineer will design, implement, and optimize data solutions in Snowflake, collaborate with clients, and mentor junior engineers.