Top Data & Analytics Jobs

Designs, builds, and operates reliable Azure data pipelines using Databricks, Azure Data Factory, PySpark, Spark SQL, and Delta Lake. Responsibilities include batch and streaming ingestion, ELT transformation, dimensional modeling, data quality enforcement, CDC, schema management, monitoring, alerting, governance, CI/CD, documentation, and operational support. Partners with architects, BI developers, and stakeholders to deliver analytics-ready datasets and improve pipeline performance, reliability, and cost efficiency.

Design and develop scalable data pipelines, data models, schemas, and integrations for a video advertising platform. Collaborate across engineering, define user stories, deliver features using AI-assisted tools, write unit tests, maintain code quality, and support production systems on a rotating schedule. The role requires strong SQL, ETL/ELT, dbt, Airflow, Snowflake, AWS, and data architecture expertise.

Leads the architecture, implementation, governance, and modernization of enterprise AWS data platforms. Designs lakehouse, batch, and real-time solutions; builds pipelines with Glue, EMR, Lambda, PySpark, SQL, and Python; optimizes Redshift and S3 workloads; and implements security, cataloging, lineage, and row-level controls. Develops reusable QuickSight dashboards, datasets, semantic layers, and AI-powered reporting components. Provides technical leadership, mentoring, migration guidance, and collaboration across business, analytics, and engineering teams.

Own and scale the company’s analytics infrastructure, including BigQuery data warehouses, dbt data marts, external data exchange, DataOps, data quality, governance, security, and cloud cost optimization. Partner with application database teams, analytics engineers, and data scientists to enable reliable metrics and scalable client data delivery.

Architects and manages enterprise knowledge repositories, database systems, and knowledge-management workflows supporting Joint Test and Evaluation programs. Collects and organizes test data, operational insights, lessons learned, and technical deliverables; develops dashboards, search tools, taxonomies, metadata, governance procedures, and version-control processes. Collaborates with test directors, analysts, military leadership, and stakeholders across classified and unclassified networks while maintaining data integrity and accessibility.

Leads enterprise data engineering solutions for financial services clients using Snowflake, Databricks, SQL, and Python. Designs and optimizes ELT/ETL pipelines, data models, analytical datasets, orchestration, governance, and performance solutions. Mentors data engineers, manages technical priorities and deliverables, reviews designs and code, and works directly with business and technology stakeholders on accounting, tax, finance, risk, and regulatory reporting initiatives.

Supports financial aid services by administering PeopleSoft Campus Solutions functionality, testing system changes, troubleshooting issues, and coordinating with Financial Aid and IT. Creates queries, reports, dashboards, and data extracts; analyzes data to maintain integrity and compliance; improves processes and student-facing functionality; and documents system procedures and requirements.

Leads customer segmentation, personalization, and customer master data strategy. Develops models, personalization roadmaps, data governance practices, and unified customer profiles to support targeted marketing and customer experience initiatives. Partners with CRM, marketing, analytics, technology, and operations teams; monitors KPIs; ensures data quality and privacy compliance; and manages a team of insights analysts and specialists.

Supports data gathering, validation, statistical analysis, reporting, visualization, financial business case analysis, and cost and process improvement initiatives. Collaborates with cross-functional teams to generate actionable insights and support data-informed decisions. The internship provides exposure to transportation and supply chain projects while developing practical analytics skills.

Build and maintain SQL data models, reporting structures, data pipelines, database architectures, and ETL/ELT workflows. Transform and validate enterprise data using Databricks, Snowflake, cloud platforms, Python, and SQL. Partner with stakeholders to translate business needs into scalable analytics solutions, dashboards, and data products. Investigate data quality issues, optimize performance, automate workflows, and apply AI-enabled analytics tools with appropriate security, governance, and human validation.