Data Engineer

Data Engineer

Department: Data

Employment Type: Full Time

Location: Pittsburgh Onsite

Compensation: $75,000 - $85,000 / year

Description

Wolfe is a Pittsburgh-based FinTech company embedding AI across its product, its internal processes, and the way its teams work day-to-day, and the Data Engineer supports that shift. Working within the Data Platform team, this role builds and maintains the pipelines and data models that turn raw source data into governed, curated datasets the organization can rely on. Day to day it integrates enterprise and marketing sources, including GA4, ad platforms, CRM, email, affiliate, and social alongside core operational systems, into trusted data products, and improves those datasets so teams can use AI-driven and self-service analytics with confidence. The role works closely with senior data engineers under Wolfe's federated hub-and-spoke governance model, taking direction on architecture and standards from the central Data Platform team while independently delivering well-defined data work.
This is a 5-day onsite role in Pittsburgh, PA.

Responsibilities

• Build and maintain ELT/ETL pipelines across the Bronze, Silver, and Gold layers of the lakehouse so data lands reliably and on schedule.
• Integrate enterprise and marketing data sources, including GA4, ad platforms, CRM, email, affiliate, and social, into governed, curated datasets.
• Build dimensional models and semantic data products, following established platform patterns, that business teams can query directly for self-service analytics.
• Implement automated data quality checks, monitoring, and observability across production pipelines, and troubleshoot failures and performance issues.
• Apply data governance standards including cataloging, lineage, tagging, and access controls, in partnership with Data Stewards and senior members of the Data Platform team.
• Prepare clean, well-structured, production-ready datasets that support AI/ML and Agentic AI workflows.

Impact Statement:

For more clarity on the role, below are the success metrics and measurements for this role in the first 90 to 120 days.:

• Onboard at least two existing data sources (for example GA4 and one ad platform or core operational system) onto governed pipelines, with documented lineage and data quality checks for each.
• With guidance from a senior engineer, ship one new dimensional model or semantic data product that a Marketing or business stakeholder uses for self-service analytics.
• Stand up automated data quality monitoring on at least one production pipeline, with alerting in place for failures and anomalies.

Qualifications

• 2-4 years of experience in data engineering, with hands-on experience building and maintaining production pipelines.
• Strong SQL and working proficiency in Python and/or Spark.
• Experience building and orchestrating pipelines with Airflow, dbt, or similar tools.
• Experience with AWS data services (Glue, S3, Athena, IAM) and cloud data warehouses (Redshift, Snowflake, or BigQuery preferred).
• Working knowledge of dimensional modeling and data governance concepts including cataloging, lineage, and access control.
• Familiarity or interest in AI/ML workflows, with exposure to Agentic AI concepts considered a plus.

Compensation, Benefits, and Perks

Wolfe is committed to providing a comprehensive benefits package to support your well-being, along with competitive compensation. Our benefits and perks include but not limited to:

• Restricted Stock Units (RSUs)
• Profit Share
• Medical, Prescription, Vision, and Dental insurance for employees and dependents (Wolfe pays 80% of premium)
• Short-Term Disability Insurance (Wolfe pays 100% of premium)
• Voluntary Long-Term Disability Insurance, Life Insurance, Critical Illness Insurance, Accident Insurance, and Hospital Indemnity coverage
• PTO (vacation and sick time)
• Corporate Holidays and Floating Holidays
• 401(k)
• Employee recognition program
• Charitable Donation to a charity of your choice yearly
• Employee Referral Bonus
• Tuition Reimbursement
• Internal Training and Information sessions
• Family Picnic, Holiday Party, and other outings
• Internal Culture Club