Top Data & Analytics Jobs in Huntsville, AL

Build and maintain web crawling and scraping pipelines to collect, transform, and deliver third-party healthcare data. Research sources, assess feasibility, implement extraction strategies, test for quality, and maintain scrapers when sources change. Participate in weekly standups and initial fundraising activity.

Build and maintain executive and project-level dashboards, standardize and cleanse source data, define reporting conventions and KPIs, perform data quality checks, coordinate with stakeholders, and apply AI/LLM tools to improve reporting workflows and efficiency.

Design, build, and optimize scalable ETL/ELT data pipelines into Snowflake using Azure Data Factory, Synapse, and ADLS. Migrate on-prem SQL Server processes to cloud, develop and tune SQL and stored procedures, implement monitoring and CI/CD, support production as part of Tier-3 on-call rotation, and collaborate with stakeholders to ensure data quality and governance.

Lead architecture and scaling of the Databricks data warehouse and self-service data platform. Build reusable batch and streaming frameworks, enforce governance, SLOs, lineage, observability, CI/CD, and multi-tenancy. Mentor engineers, run design reviews, and ship documented patterns to enable analytics, data science, and app teams to move quickly without blocking on platform tickets.

Build end-to-end data and analytics features: ingest and model data, build transformations and pipelines, create client-facing dashboards and interfaces, and develop LLM-powered workflows to accelerate analysis and app development. Partner with stakeholders, perform exploratory analyses, and ensure data quality, observability, and maintainability while influencing data engineering strategy.

Manage end-to-end analytics projects, lead cross-functional teams, ensure client satisfaction, and utilize AI tools to enhance data insights.

Design and improve learning data reporting and dashboards in Cornerstone, integrate Cornerstone and Workday data, conduct user research and usability testing, create wireframes and prototypes, design accessible reporting interfaces, and collaborate with L&D, HR, product, and technical teams to optimize reporting and UX.

Lead end-to-end customer engagements to architect, implement, and optimize large-scale Spark/Databricks workloads. Troubleshoot and tune PySpark and DBSQL jobs, design PoCs and workshops, advocate strategically for customers, collaborate cross-functionally, and mentor junior engineers on Lakehouse best practices.

Lead customer engagements to architect, implement, and optimize large-scale Spark and Databricks workloads. Troubleshoot and tune distributed PySpark and DBSQL jobs, design PoCs/workshops, advocate technical solutions, mentor junior engineers, and collaborate cross-functionally to improve platform features and cost-efficiency.

Lead professional services projects to design, build, and deploy production-grade Databricks Big Data and AI solutions. Write production Python/Scala code, optimize Apache Spark workloads, design CI/CD and MLOps pipelines, advise on architecture and build vs buy decisions, and resolve complex performance issues while collaborating with product engineering.

Senior individual contributor responsible for designing and aligning data solutions for commercial profitability and enterprise platforms. Translate business outcomes into scalable technical designs, guide development teams on best practices, ensure alignment with enterprise architecture and governance, standardize data models, and collaborate with product, finance, and technology stakeholders to deliver accurate, performant, and reusable data assets.

Partner with HR, Finance, and business leaders to model future workforce needs, run scenario analyses, build workforce simulations and dashboards, and provide data-driven recommendations to inform talent strategy and organizational design.

Lead definition and operationalization of enterprise data consumption and semantic layer standards across the Lakehouse. Build certified datasets, semantic models, and governed data products to enable consistent, high-performance reporting and self-service analytics across Tableau, Power BI, WebFocus and other BI tools. Partner with governance, define SLAs, and drive adoption, performance optimization, and a single source of truth for enterprise metrics.

Design, build, and optimize end-to-end ETL/ELT pipelines using Python and PySpark for large structured and unstructured datasets. Ensure data quality through validation and reconciliation, troubleshoot performance issues, implement CI/CD and code review practices, and collaborate with IT and business stakeholders to translate requirements into scalable data solutions.

Lead design and implementation of data ingestion, data lake, and ETL solutions using Big Data technologies. Build performant cloud data pipelines, integrate multiple data sources, optimize query performance, enable analytics and data science teams, and lead offshore engineering teams.