Top Data & Analytics Jobs

Designs, deploys, maintains, scales, and supports enterprise database systems, primarily PostgreSQL in Linux environments. Responsibilities include database architecture, tuning, backup and recovery, failover, large-scale data management, ETL, operational support, testing with real data, and developing system features. The role also explores emerging technologies, supports customer facilities, and may contribute to cloud, DevOps, GIS, APIs, dashboards, and web development.

Provide analytic and consultative support to internal customers; translate requirements into decision-support applications; model data flows; develop complex programs and reports (SAS, R, SQL) using enterprise databases; propose and lead data-driven solutions; prepare findings and presentations for stakeholders; define data policies and security frameworks.

Designs, builds, and optimizes scalable ETL/ELT pipelines, data models, semantic layers, warehouses, lakehouses, and streaming architectures. The role supports enterprise analytics, reporting, and AI/ML initiatives while ensuring data quality, governance, security, lineage, and metadata management. Responsibilities include translating business requirements into reliable data solutions, maintaining documentation and standards, and collaborating with stakeholders and governance teams.

Builds and supports data conversion, enterprise BI, reporting, data pipelines, and warehouse integrations across legacy and modern County systems. Responsibilities include cleansing and validating data, developing Power BI dashboards and paginated reports, creating Azure Databricks and Data Factory pipelines, tuning Oracle and SQL Server solutions, modeling data with DAX/MDX, supporting Oracle financial-system integrations, documenting controls, and enabling business-user adoption.

Designs scalable data models, optimized SQL queries, analytics infrastructure, semantic layers, and data applications. Partners with data science, product, engineering, and business teams to enable dashboards, self-service analytics, reporting, and enterprise data-driven decision-making. The role also establishes analytics engineering best practices, improves developer experience, and supports secure, compliant data warehousing.

Serves as the bridge between retail business stakeholders and the enterprise data ecosystem. Builds Tableau dashboards and Snowflake SQL analyses, defines data requirements, oversees third-party data engineering pipelines, validates data quality, documents data flows, supports self-service reporting, and establishes BI governance standards. The role focuses on omnichannel retail systems including Shopify, NetSuite, Manhattan WMS, Klaviyo, and Google Analytics while ensuring privacy and regulatory compliance.

Administers the Raiser's Edge NXT donor database, ensuring data integrity, security, maintenance, reporting, integrations, and process improvement. Builds dashboards, reports, queries, and fundraising insights; trains staff; manages Blackbaud vendor support; coordinates system upgrades and integrations; and supports Finance with reconciliations, audits, and Form 990 reporting. The role also documents procedures, develops automation, and manages database requirements across departments.

Lead the data engineering foundation for MCG’s AI products. Build and operate data platforms, ingestion and transformation workflows, governed datasets, dashboards, and reliable production pipelines. Partner with Product, Engineering, Data Science, and customers to translate needs into technical solutions, support machine learning lifecycles, identify insights, and inform AI product decisions and roadmaps.

Design, build, and operate Databricks Lakehouse pipelines (Bronze/Silver/Gold) using Delta Lake and DLT. Optimize Spark/SQL workloads and Delta tables for performance and cost, implement incremental processing with exactly-once semantics, ensure data quality, and deliver documented datasets and dashboards (Power BI/other) with SLAs. Collaborate with cross-functional teams, integrate real-time sensor data, and support stakeholders. Occasional travel; primarily on-site.

Lead business intelligence strategy across product, clinical, commercial, finance, and engineering teams. Build measurement frameworks, semantic layers, reporting solutions, and visualizations that demonstrate business value and support data-informed decisions. Own the data lifecycle from ideation through client-facing delivery, ensure data governance and integrity, and translate complex datasets into actionable insights. Collaborate on scalable data architecture and apply statistical methods, advanced analytics, and emerging AI-driven BI capabilities.