Top Data & Analytics Jobs in Atlanta, GA

The Senior Analyst in AML KYC will conduct detailed customer onboarding, monitor client relationships for compliance, and update KYC records while utilizing AI tools for efficiency.

Design and build data validation, integration, and transformation solutions to support ERP implementations and risk/regulatory clients. Develop data pipelines and infrastructure, manage data validation processes, ensure data lineage and quality, manipulate large datasets using Excel, Alteryx, SQL, Python, Databricks, or Snowflake, and collaborate with clients to deliver scalable, governed data solutions.

The VP of Alternative Data Strategy drives sourcing, prioritisation, and implementation of alternative datasets, aligning data opportunities with investment strategies and governing data usage across teams.

Entry-level Junior Data Engineer to help build and maintain cloud data pipelines into BigQuery using tools like Fivetran and Python. Contribute to Medallion (bronze/silver/gold) layers, data transformations (dbt), basic data quality checks, CI/CD practices, documentation, and governance while learning cloud engineering, orchestration, and observability under senior engineers.

Design, build, and maintain scalable data systems and pipelines (batch and streaming). Implement data formats, modeling, and infrastructure; support deployment automation, stakeholder requirements, and data governance to enable analytics and reporting.

Serve as a strategic, hands-on BI partner connecting business strategy to data across the lifecycle. Translate leadership directives into actionable requirements, map and unify data from disparate sources, ensure data governance and schema alignment, collaborate with Data Engineers/Architects and business stakeholders, produce reliable datasets/reports, investigate data quality issues, and manage projects end-to-end to deliver actionable insights.

Lead the design and implementation of enterprise-scale Knowledge Graphs and Semantic AI solutions, integrating graph intelligence and Generative AI. Manage cross-functional teams in data architecture and governance.

As a Data Platform Engineer, you'll architect and implement data services, build data pipelines, optimize for real-time risk assessment, ensure data governance, and collaborate across teams.

Lead and develop a team delivering data conversion for customer implementations. Drive adoption of AI and automation, manage complex/at-risk migrations, track KPIs, and improve processes through experimentation and transformation.

Design and implement scalable batch and near-real-time data pipelines and storage on AWS. Define data architecture, ensure observability, optimize performance, lead production troubleshooting and migrations, enforce CI/CD and deployment best practices, and collaborate with stakeholders and platform teams to align solutions with business needs.

Lead design and governance of KPIs, semantic layers, and analytics assets. Perform advanced SQL tuning across RDS/Oracle/Redshift and cost-aware Athena querying. Build reproducible Python analyses, data validation, anomaly detection, deep-dive analytics, source-to-target mapping, and drive BI dashboard UX and version-controlled analytics engineering practices.

Assist in building and maintaining ETL pipelines using Python and PySpark; develop workflows with AWS Glue, Lambda, and Step Functions; work with S3, Redshift, RDS, and Oracle; write complex SQL for extraction, transformation, and reporting; implement monitoring, logging, and error handling; ingest API/JSON data; collaborate with engineers, analysts, and stakeholders; support code management, documentation, and deployments.