Top Data & Analytics Jobs

Build and lead complex data integration projects from client onboarding through ongoing platform usage. Analyze and resolve data discrepancies, troubleshoot SIS and SSO integrations, develop internal Retool applications, perform code reviews, prioritize backlogs, manage projects, and mentor teammates. The role requires advanced SQL, development expertise, technical leadership, and collaboration with internal stakeholders, with Ruby on Rails, AWS, Git, and K-12 education experience preferred or desired.

Designs, develops, and optimizes enterprise data platforms, ETL workflows, databases, reporting solutions, and dashboards. Leads technical designs, SDLC processes, troubleshooting, documentation, and production support while collaborating with stakeholders and vendors. Uses SQL Server, SSIS, T-SQL, Microsoft BI tools, and DevOps technologies to build scalable, reliable data integration and business intelligence solutions. Supports cloud migration and may use Azure, Fabric, Snowflake, or Databricks.

Support analytics initiatives by gathering, cleaning, modeling, and analyzing data. Produce forecasts, reports, and visualizations, document data and processes, and present actionable insights to influence leadership decisions while improving data quality and management.

Designs and develops complex BI reports and dashboards, implements business rules, defines KPIs and governed data sources, performs statistical modeling and ad hoc analysis, coordinates with IT and embedded analysts to deliver analytics solutions for partners, legal staff, and firm management.

Designs, develops, and maintains enterprise databases, ETL workflows, data platforms, reporting systems, and business intelligence solutions. Leads technical design, data integration, automation, troubleshooting, documentation, and production support. Collaborates with stakeholders and vendors to deliver scalable, secure, and reliable data solutions. Requires advanced SQL Server, SSIS, T-SQL, and SDLC expertise, with preferred experience in Microsoft BI tools, APIs, cloud data services, and Python or Java.

Leads the enterprise data and analytics platform organization, defining strategy, architecture, roadmaps, governance, engineering standards, and operating models. Oversees scalable cloud data capabilities supporting analytics, AI, and machine learning while partnering with senior stakeholders and managing vendors. Builds globally distributed technical teams, drives platform adoption and self-service capabilities, and delivers measurable business outcomes through secure, governed, and reliable data platforms.

Develop and support analytical systems for operational decision-making, identify KPIs with business process owners, analyze data lifecycles, define data warehouse and ETL requirements, validate data engineering results, build dashboards, and present insights to customers. The role requires at least one year of data or BI analyst experience, strong SQL and data visualization skills, analytical communication abilities, and fluency in Russian and English.

Build and maintain production analytics data models using dbt, improving data quality, documentation, testing, and performance. Partner with analysts, data scientists, engineers, and business stakeholders to define metrics and translate ambiguous questions into scalable data solutions. Promote engineering best practices through solution design, code review, and collaboration. Use Fivetran and Stitch for data ingestion while supporting reporting, experimentation, and operational decision-making.

Support the design, development, automation, monitoring, and optimization of enterprise-scale data platforms and pipelines. Build logging, metrics, and alerts; collaborate with product and application teams on data models and schemas; maintain production data integrity; and analyze complex business problems to deliver actionable insights. The role also requires balancing competing priorities and communicating effectively with technical and business stakeholders.

Build and manage dashboards and analytics (equipment/OFCI, construction, commissioning, readiness) using data from enterprise systems to surface lifecycle risks, inform TCO and procurement decisions, and lead an analyst team supporting cross-functional planning.