Data Engineer

Location: New York, NY — Hybrid, 3 days onsiteExperience: 4–10 yearsCompensation: $160,000–$170,000 base + $24,000–$25,500 bonusIndustry: FinTechAbout the RoleWe’re looking for a hands-on Senior Data Analyst / Data Engineer to join a growing data organization at a leading FinTech company.

This is a hybrid role for someone who can work across data engineering, business intelligence, analytics, and data quality.You’ll serve as a key connection point between business stakeholders and technical data teams, transforming complex data into actionable insights while helping build and maintain scalable, trusted data infrastructure.The ideal candidate is highly technical with SQL and Python, experienced with ETL/ELT and cloud data warehouses, and comfortable building dashboards and working directly with business stakeholders.What You’ll DoBusiness Intelligence & AnalyticsBuild and maintain executive dashboards, reports, and scorecards using Tableau and SnowflakePartner with Finance, Sales, Operations, Product, and Customer Success to translate business needs into data-driven solutionsPerform ad hoc analysis to identify trends, opportunities, and operational improvementsDefine and standardize KPIs and business metrics across the organizationPresent insights and recommendations to business stakeholders and leadershipData Engineering & IntegrationDevelop SQL-based data transformations, views, and stored procedures within SnowflakeBuild and maintain ETL/ELT pipelines from sources including PostgreSQL, SQL Server, Salesforce, APIs, and Amazon S3Validate data ingestion processes for accuracy, completeness, and consistencyTroubleshoot pipeline and data-quality issues and perform root-cause analysisOptimize SQL queries, data models, and reporting structures for performance and scalabilityContribute to dimensional modeling and curated reporting datasetsWork across development, QA, staging, and production environments following SDLC and change-management processesData Quality & GovernanceMonitor and improve enterprise data quality by identifying anomalies, inconsistencies, and reconciliation issuesDevelop validation processes and reconciliation reporting between source systems and SnowflakeMaintain data definitions, dictionaries, metadata, and documentationPartner with business and engineering teams to establish data standards and governance practicesAI & Advanced AnalyticsSupport semantic models that power AI and enterprise data applicationsImprove metadata, business definitions, and synonyms to increase the accuracy of AI-generated insightsEvaluate and support emerging AI capabilities that improve analytics, reporting, and business decision-makingWhat We’re Looking For4–10 years of experience in Data Engineering, Data Analytics, Business Intelligence, or Analytics EngineeringStrong hands-on SQL skills, including complex queries, CTEs, views, stored procedures, and query optimizationExperience with Snowflake or another cloud data warehouseExperience with Tableau or a comparable BI platformStrong understanding of ETL/ELT and modern data architecturesHands-on experience with Python for data analysis, automation, or data engineeringExperience working with APIs and semi-structured data, including JSON, XML, or ParquetExperience with AWS services such as S3, Glue, or Lambda is a plusFamiliarity with Git, SDLC processes, and Agile methodologiesStrong analytical, problem-solving, communication, and stakeholder-management skillsWhy This Role?This is an opportunity to work across the full data lifecycle — from source systems and data pipelines through Snowflake, transformation, data quality, BI, semantic models, and AI-enabled analytics.You’ll have meaningful exposure to both the technical data environment and business side of the organization, making this a strong opportunity for someone who wants to operate beyond traditional reporting and analytics.