Top Senior Analysis Reporting Jobs in Atlanta, GA

Lead SAP data workstream for ECC to S/4HANA Brownfield migrations: define strategy and roadmap; oversee extraction, profiling, cleansing, transformation, reconciliation, and validation of master and transactional data; run mock conversions, cutover planning, and post-go-live reconciliation; establish data quality, governance, stewardship, controls, and training; manage risks, defects, and stakeholder reporting.

Design, build, and maintain Databricks-based data platform and ETL/ELT pipelines. Collaborate with stakeholders, implement data quality checks and testing, monitor pipeline performance, document architecture, and coordinate cross-functional teams.

Administer and monitor AWS PostgreSQL databases, optimize complex queries, review schemas and indexes, guide data architecture, support releases and infrastructure growth, and maintain RDS systems. The role also automates manual workflows using AI tools, collaborates cross-functionally, and mentors junior and mid-level engineers while establishing database best practices.

Own the Industrial platform’s data infrastructure, datasets, dashboards, models, and AI-enabled analytical workflows. Deliver investor and occupier business-development insights, supply-chain mapping, surveys, executive reporting, presentations, and pursuit support. Partner with Research, Sales Enablement, technology, operations, brokers, and leadership to improve data integrity, self-service reporting, platform capabilities, and automation. Coordinate cross-functional initiatives and translate quantitative analysis into actionable narratives for senior leaders and clients.

The Senior eDiscovery Analyst advises litigation teams and clients on ESI preservation, collection, processing, review, analysis, and production. The role manages Relativity applications, develops discovery databases and documentation, troubleshoots data, and supports cloud and collaboration data sources. It designs and validates Relativity aiR workflows, mentors analysts on generative AI, and ensures defensible review practices. The analyst also manages multiple projects, maintains technical expertise, supports clients and vendors, works Eastern Time hours, and meets a 1,400-hour annual billable goal.

Leads healthcare trend and actuarial analytics, investigating cost, utilization, financial, clinical, and operational drivers. Develops pricing, risk, valuation, reporting, dashboard, and forecasting analyses; translates complex findings into recommendations for leaders and business partners. Manages complex analytical projects, improves methodologies, and advances AI, automation, and visualization adoption. Provides actuarial support for product design, legislation, claims, premiums, enrollment, experience-rating formulas, and risk-sharing models while mentoring junior analysts.

Lead collection, cleansing, mapping, and storage of data from multiple sources; analyze data using statistical methods; create visualizations and reports; resolve discrepancies and ensure data quality; lead projects, influence executive decisions, and mentor junior staff.

Architects and implements scalable data pipelines and enterprise data solutions spanning data lakes, warehouses, marts, and distributed systems. Designs dimensional and semantic data models, curated datasets, and Power BI reporting solutions with DAX, security, governance, and performance optimization. Establishes data lineage, metadata, stewardship, compliance, and secure access practices. Collaborates with stakeholders to translate business and reporting requirements into reusable analytics assets, while supporting AI and MLOps data pipelines across cloud and hybrid platforms.

Leads and coaches a data engineering team while contributing hands-on to platform architecture, data modeling, ETL pipelines, data quality, and analytics solutions. Designs trusted facts, dimensions, snapshots, and slowly changing dimensions using Snowflake, Databricks, dbt, and Airflow. Partners with stakeholders, security teams, vendors, and cross-functional groups on data strategy and controls, resolves production issues, supports incident response, and develops engineering talent.

Lead enterprise-scale data engineering initiatives, including the design, development, deployment, and maintenance of production data pipelines and scalable data platforms. Guide multidisciplinary teams, modernize analytics workflows using Python and SQL, develop shared libraries, and support Palantir Foundry adoption through training, integration, and architecture. Collaborate with stakeholders, provide technical presentations, and apply expertise in data architecture, Databricks, cloud platforms, and distributed data processing.