Data Engineer

Location: New York, NY — Hybrid, 3 days onsite

Experience: 4–10 years

Compensation: $160,000–$170,000 base + $24,000–$25,500 bonus

Industry: FinTech

About the Role

We’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 Do

Business Intelligence & Analytics

• Build and maintain executive dashboards, reports, and scorecards using Tableau and Snowflake
• Partner with Finance, Sales, Operations, Product, and Customer Success to translate business needs into data-driven solutions
• Perform ad hoc analysis to identify trends, opportunities, and operational improvements
• Define and standardize KPIs and business metrics across the organization
• Present insights and recommendations to business stakeholders and leadership

Data Engineering & Integration

• Develop SQL-based data transformations, views, and stored procedures within Snowflake
• Build and maintain ETL/ELT pipelines from sources including PostgreSQL, SQL Server, Salesforce, APIs, and Amazon S3
• Validate data ingestion processes for accuracy, completeness, and consistency
• Troubleshoot pipeline and data-quality issues and perform root-cause analysis
• Optimize SQL queries, data models, and reporting structures for performance and scalability
• Contribute to dimensional modeling and curated reporting datasets
• Work across development, QA, staging, and production environments following SDLC and change-management processes

Data Quality & Governance

• Monitor and improve enterprise data quality by identifying anomalies, inconsistencies, and reconciliation issues
• Develop validation processes and reconciliation reporting between source systems and Snowflake
• Maintain data definitions, dictionaries, metadata, and documentation
• Partner with business and engineering teams to establish data standards and governance practices

AI & Advanced Analytics

• Support semantic models that power AI and enterprise data applications
• Improve metadata, business definitions, and synonyms to increase the accuracy of AI-generated insights
• Evaluate and support emerging AI capabilities that improve analytics, reporting, and business decision-making

What We’re Looking For

• 4–10 years of experience in Data Engineering, Data Analytics, Business Intelligence, or Analytics Engineering
• Strong hands-on SQL skills, including complex queries, CTEs, views, stored procedures, and query optimization
• Experience with Snowflake or another cloud data warehouse
• Experience with Tableau or a comparable BI platform
• Strong understanding of ETL/ELT and modern data architectures
• Hands-on experience with Python for data analysis, automation, or data engineering
• Experience working with APIs and semi-structured data, including JSON, XML, or Parquet
• Experience with AWS services such as S3, Glue, or Lambda is a plus
• Familiarity with Git, SDLC processes, and Agile methodologies
• Strong analytical, problem-solving, communication, and stakeholder-management skills

Why 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.