Top Remote Data & Analytics Jobs in Dallas, TX

Design, develop, maintain, and optimize ADABAS database structures and data solutions. Support mainframe data processing (Natural, COBOL, JCL), perform migrations to modern platforms, tune performance, ensure data integrity/security, troubleshoot issues, and collaborate with developers, architects, and analysts on modernization, API/cloud integration, and data warehousing initiatives.

Remote SQL Developer responsible for developing and maintaining critical SQL code, schemas, ETL pipelines, and data transformations. Tasks include writing complex stored procedures, schema/index design, query tuning, backup/restore, processing varied source formats, validating data, supporting stakeholders, and contributing to data engineering tooling and deployment practices in an agile startup environment.

The Biostatistician designs, analyzes, and interprets clinical trial data, collaborating with various teams and ensuring statistical rigor and compliance with regulatory standards.

Investigate financial transactions to identify potential money laundering activities, utilize AI for analysis, document findings, and collaborate with product teams on improvements.

As a Lead Data Engineer, you'll optimize data workflows, manage data engineering projects, mentor junior engineers, and ensure robust data solutions meet business needs.

The Data Architect will require extensive experience in Data Engineering, consulting, and leading technical teams, focusing on data warehousing and various technologies.

Analyze large federal and state economic datasets, automate data collection and scraping, and rapidly publish clear, data-driven reporting on market-moving indicators. Collaborate with reporters and visual journalists, file public-records requests, and use emerging technologies including AI to enhance real-time coverage.

Lead strategic analytics and partner with senior leadership to drive growth, margin, and retention initiatives. Build interactive reporting (Python/Streamlit, BigQuery-connected Google Sheets), perform deep EDA in Jupyter, model and clean data with SQL and dbt, integrate secure AI-assisted tools and automation, ensure analytical quality, and translate insights into measurable business outcomes.

Own and maintain the companys data infrastructure and pipelines. Design, build, and monitor ETL/ELT workflows and data architecture; integrate SaaS sources; enforce data quality, standards, and governance; partner with stakeholders to deliver analytics-ready data and meet data availability SLAs.

Design and build large-scale data migration systems, map heterogeneous legacy sources into the platform, ensure end-to-end data correctness, create repeatable tooling, support analytics and BI, optimize performance and storage, debug production data issues, and collaborate with Product, Implementation, and Ops for agency onboarding.