Top Data & Analytics Jobs

The Lead Data Engineer designs and oversees data systems to facilitate data-driven decisions, collaborating with teams to build scalable data infrastructure and tools.

The role involves developing and integrating cloud-native data services and APIs, supporting data transformation, and maintaining backend services using AWS technologies.

Lead design and implementation of batch and streaming data pipelines, build data models, implement data quality and testing, manage orchestration and IaC, mentor engineers, and communicate technical direction and tradeoffs to stakeholders.

As a Senior Data Engineer, you will design AI-optimized data platforms, build data pipelines, and collaborate on analytics projects, while advising clients on data architecture.

Lead design, implementation, and optimization of data pipelines, models, reports and Power BI/SSMS dashboards for public safety clients. Configure analytics databases, train agency users, produce instructional materials, mentor junior engineers, and serve as technical SME and escalation point for multi-agency analytics implementations.

Lead analytics implementations for public safety clients: build and optimize data pipelines, models, Power BI/SSMS/SSRS reports and dashboards; train users, create eLearning and instructional materials, mentor junior engineers, and serve as primary technical SME for crime analytics and customer escalations.

Design, build, and maintain data pipelines, models, reports and Power BI/SSMS dashboards for public safety clients. Configure system databases, optimize queries and data models, train agency users, create instructional materials and eLearning, lead multi-agency implementations, mentor junior staff, and serve as the analytics SME and escalation point while ensuring CJIS compliance.

Design, configure, and optimize analytics databases, pipelines, models, reports and Power BI/SSMS dashboards for public safety customers. Train agencies, create instructional materials and eLearning, lead multi-agency implementations, mentor junior staff, and act as technical SME and escalation point. Leverage AI tools to accelerate SQL and dashboard development and collaborate with product and stakeholders to maintain solutions.

Design, build, and maintain data pipelines, models, and Power BI/SSMS reports for public-safety clients; configure system databases, optimize queries, train agencies, create instructional materials, leverage AI tools, lead multi-agency implementations, mentor junior staff, and act as the primary analytics SME and escalation point.

Design, build, and optimize data pipelines, models, reports and Power BI/SSMS dashboards for public safety customers. Lead complex analytics implementations, train agency users, create instructional content, mentor junior staff, and serve as technical SME while ensuring performance, security (CJIS), and customer support.

The Sr. Data Engineer will build and manage data pipelines for large datasets, collaborate with teams, and leverage cloud technologies for data processing.

Lead Data Engineer responsible for defining architecture, engineering standards, and best practices for the enterprise data platform, collaborating with distributed teams for modernization and scalability.

Lead design and delivery of cloud-native data pipelines and data warehouse models for insurance analytics using Snowflake, PySpark, and AWS. Drive migration/modernization from legacy systems, implement SQL transformations and data quality frameworks, optimize performance, and enforce engineering standards. Coordinate onshore/offshore teams, engage stakeholders, mentor junior engineers, and support project planning and delivery.

Lead data migration and engineering efforts: design, build, operationalize, and maintain enterprise-scale ETL/ELT pipelines and data platforms. Execute full migration lifecycle, optimize Informatica workflows, support CI/CD/DevOps, ensure data validation/security, and collaborate on cloud (AWS) and database migrations.

Design, build, and operate scalable ingestion, curation, and metadata-enrichment pipelines for enterprise data catalog and discovery. Ensure data quality, schema evolution, lineage, and cost-efficient large-scale processing; translate technical concepts for non-technical stakeholders and support downstream mission use.

As a Senior Data Engineer, you'll design and maintain scalable data pipelines, optimize workflows with dbt and Snowflake, and mentor teams across functions to enhance data reliability and performance.

Design, build, and operate Persona's large-scale data platform: datalake and lakehouse, streaming and batch ingestion (including CDC), high-throughput data-movement services, real-time serving layer, and query/analytics capabilities. Drive architecture decisions, performance, reliability, and cost, and lead multi-quarter infrastructure projects while mentoring engineers and partnering with infrastructure, data science, and product teams.

The Snowflake Data Engineer will work on data cleansing and harmonization, moving from legacy systems to SAP S4, focusing on ETL/ELT development and view creation.

The AWS Data Engineer will work on a data cleansing and harmonization project, focusing on AWS ETL design and development using various AWS services.

This role involves designing, building, and maintaining data pipelines on Snowflake. Responsibilities include ensuring data quality and collaborating with stakeholders to deliver solutions.

The Snowflake Data Engineer will design, build, and maintain data pipelines on Snowflake, optimizing performance and ensuring data quality while collaborating with stakeholders.

The Snowflake Data Engineer and Product Owner will manage the Snowflake data analytics project, collaborating with stakeholders, leading Agile practices, and ensuring quality deliverables through effective team coordination and backlog management.

The Cloud Data Engineer will design, implement, and manage data solutions on Microsoft Azure, create and maintain data pipelines, and ensure data security for decision-making processes.

Develop custom connectors on Airbyte for data ingestion from various platforms, ensuring accurate data integration and transformation. Collaborate with stakeholders and perform testing for reliability.

The role involves building and managing robust data pipelines, optimizing data infrastructure, ensuring data quality, and integrating operational data systems. Collaboration with stakeholders and applying engineering best practices are essential, including expertise in cloud computing and various data formats.