Top Remote Data & Analytics Jobs in Louisville, KY

Design, build, and maintain scalable ETL/ELT pipelines and data models using Databricks, Spark, dbt, SQL, and AWS services. Optimize ingestion, transformation, orchestration, and monitoring across structured and semi-structured data. Collaborate in Agile teams, support analytics and reporting for large-scale federal environments, and evaluate new data tools and platform improvements.

Design, build, and maintain scalable AWS-native data platforms and ETL/ELT pipelines using Databricks, Spark, Python, dbt, and SQL. Implement ingestion, transformation, orchestration, and analytics solutions (Iceberg, Parquet, Redshift, Athena), support FedRAMP/NIST controls, migrate legacy systems to cloud-native services, and mentor junior engineers while collaborating in Agile teams.

Design, build, and maintain scalable ETL/ELT data pipelines and analytical platforms on AWS and Databricks. Migrate legacy workflows to cloud-native services, implement data lake and catalog solutions, enable AI/RAG/vector search, ensure FedRAMP/NIST compliance, optimize performance, and mentor junior engineers while collaborating in Agile teams.

Design, build, and maintain end-to-end batch and streaming data pipelines; develop ETL/ELT workflows and modular Python code; write and optimize SQL; implement analytics data models; monitor data quality, troubleshoot failures, and document pipelines; collaborate with stakeholders and mentor teammates. Remote role for candidates based in Latin America.

Designs, builds, and maintains scalable batch and streaming data pipelines, ETL/ELT workflows, data models, and Python transformations. Writes optimized SQL, monitors pipeline reliability, troubleshoots failures, implements data-quality validation, and supports security and governance practices. Collaborates with engineers, analysts, stakeholders, and clients to define data contracts, improve platforms, document lineage, and deliver reliable analytics data.

The role involves leading global forecasting and performance management, setting standards, overseeing processes, collaborating with cross-functional teams, and developing a high-performing team in the oncology biotech sector.

Lead analytical efforts in Real World Data research, develop specifications and methodologies, manage projects, and communicate findings to stakeholders.

The Senior Statistical Programmer will program and validate datasets for clinical trials, oversee deliverables, manage projects, and ensure compliance with industry standards. Requires strong skills in SAS and R for statistical programming.

Lead client-facing Collibra implementations across data governance, metadata management, catalogs, glossaries, workflows, and stewardship. Facilitate discovery and design workshops, translate requirements into scalable Collibra designs, configure and develop platform capabilities, drive integrations and testing, and coach client teams for adoption and sustainment.

Lead and deliver enterprise Collibra data governance implementations: design operating models, configure Collibra, integrate with enterprise systems, guide stewardship and metadata practices, mentor teams, run workshops, support pre-sales, and drive adoption and documentation.

The Business Intelligence / Data Analyst will optimize the data reporting pipeline using Google Big Query and Omni, work with product management, implement reports, and conduct ongoing maintenance.

As an Analytics Lead, you will manage the measurement strategy, oversee tracking architecture, design testing frameworks, and create insights for clients. You'll lead a junior specialist and ensure data integrity across client accounts. Responsibilities include building dashboards, interpreting metrics, and creating measurement plans to drive business decisions.

The Sr. FWA Analyst identifies fraud, waste, and abuse in medical billing through data analysis, supporting engineering and data science teams with validation and tuning of detection algorithms.

Design and deliver Databricks-centric data architectures, lead pre-sales and billable engagements, build end-to-end data engineering pipelines for AI/ML and BI, mentor teams, ensure data governance/security/quality, and resolve data system issues while producing solution documentation and presentations.

Lead Oracle Cloud reporting initiatives, ensuring data accuracy and performance while mentoring junior analysts and collaborating with stakeholders.