Top Data & Analytics Jobs

Design and maintain scalable ETL/ELT pipelines, develop data solutions using Databricks and Snowflake, and collaborate with cross-functional teams to ensure data quality and performance optimization.

Design, develop, and manage data infrastructure for internal and client projects, focusing on large-scale data pipelines, APIs, and cloud deployments.

The Data Engineer II designs, develops, and maintains data integration and analytics solutions, ensuring data quality and accessibility for business stakeholders, while collaborating with teams to meet business needs.

The Data Engineer will design, develop, and implement data solutions, ensuring data integrity and availability, collaborating with stakeholders to meet business analytics needs.

The Data Engineer will design and implement ETL frameworks, perform data analysis, troubleshoot data issues, and optimize data models to meet business needs.

Lead large-scale migration of document-heavy legacy systems into cloud, convert unstructured documents to analytics-ready data, build MuleSoft integrations and APIs, apply DataWeave transformations, ensure data quality, lineage, governance, and support Salesforce Data 360 implementation and cutover in Agile teams.

Build and maintain knowledge-graph solutions: design graph data models, implement and query graph databases, script ETL tasks, work across Linux/Mac/Windows, collaborate with software teams, operate in classified SCIF environments, and communicate system usage to analysts and senior stakeholders.

Build Power BI solutions from scratch: gather business requirements, design UI/UX dashboards, implement advanced DAX and SQL Server (T-SQL) models, and create Copilot/Copilot Studio agents and Power Automate flows. Present insights to non-technical stakeholders, consult with business SMEs, and work onsite in Atlanta (hybrid, 4 days/week).

Own and evolve the data platform by leading architectural evolution, collaborating with teams for strategic data initiatives, and ensuring reliable data systems.

Supporting Regulatory Reporting in the capital markets sector, focusing on Axiom SL implementation and integration with Hadoop as a data repository.

Design, build, and scale streaming and batch data pipelines, embedding workflows, and vector store integrations to support AI applications. Implement AI-optimized data models, ensure observability and data quality, and collaborate across infra, ML, and product teams while mentoring engineers and delivering production-ready, reliable data foundations.

The Senior Data and Solutions Engineer develops data pipelines, manages analytics frameworks, and collaborates with stakeholders to improve data quality and reporting consistency.

Founding member of a data engineering team building a Databricks-first, multi-tenant lakehouse. Design and implement batch ingestion, tenant-isolated data models, provenance-aware pipelines, nightly profile enrichment, dbt transformations, orchestration, and AI enablement for agents, RAG search, APIs, and exports.

Develop and maintain system integrations, data warehousing, automated reporting and dashboards to support compliance analytics. Perform data profiling, root-cause analysis of inconsistencies, QA completed work, document data models and technical designs, participate in Scrum ceremonies, support product management and process improvement, and lead cross-functional analyses and stakeholder communication.

As a Software Engineer in the Data Platform team, you will implement data governance frameworks, manage access controls, improve data quality, and support audit readiness.

Hands-on Senior Data Engineer to maintain and optimize an Oracle-centric enterprise data warehouse, manage cloud-to-Oracle integrations, evolve ETL/ELT pipelines, and help build a hybrid lakehouse (Apache Iceberg, OCI Object Storage, Parquet). Requires performance tuning, Linux administration, Java debugging, and close collaboration with senior client stakeholders. Contractor role with possible conversion to full-time.

Build and own large-scale data infrastructure and ingestion pipelines, partner with data science, analytics, and business stakeholders to create data products, support executive reporting, and design scalable ETL processes while ensuring data security and cross-functional collaboration.

Design, build, and maintain scalable ELT/ETL data pipelines using dbt and Prefect; optimize Snowflake performance; implement data quality, security, and observability; collaborate with analysts and data scientists; document data flows and ensure reliable ingestion from external sources.

Design and manage scalable data pipelines and infrastructure, implement ETL/ELT processes, and collaborate with teams to ensure data quality and accessibility.

The Data Engineer will architect and maintain modern data platforms, manage ETL/ELT pipelines, integrate diverse data sources, and champion data governance while supporting advanced analytics and AI workloads.

The role involves building and maintaining financial data pipelines in Databricks, bridging Snowflake, and ensuring data accuracy for finance reporting.

As a Founding Data Engineer, you'll build ETL pipelines, design scalable data models on AWS, and process complex healthcare data to improve patient care.

Build and maintain ETL pipelines and workflows to process cloud billing data. Design data storage systems and develop validation systems to ensure data quality.

As a Senior Data Engineer, you'll design data pipelines, develop analytics ecosystems, and integrate AI/ML capabilities for mission-driven projects, guiding teams in an agile environment.

The Data Engineer will design and build data pipelines and platforms, mentor teams, and implement AI/ML solutions for various high-impact projects, primarily in secure environments.