Data Engineer

Wolfe, LLC is a Pittsburgh-based FinTech company that embeds AI across its products and internal operations. In the Data Platform team, this Data Engineer role focuses on building governed data pipelines and data models that turn enterprise and marketing sources into trusted datasets for analytics, AI/ML, and Agentic AI workflows.

What you’ll do

• 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 sources, including GA4, ad platforms, CRM, email, affiliate, and social, into governed and curated datasets.
• Create dimensional models and semantic data products using established platform patterns so business teams can query data directly for self-service analytics.
• Implement automated data quality checks, monitoring, and observability across production pipelines, then troubleshoot pipeline failures and performance issues.
• Apply data governance standards, including cataloging, lineage, tagging, and access controls, working with Data Stewards and senior Data Platform team members.
• Deliver clean, well-structured, production-ready datasets that support AI/ML and Agentic AI workflows.

Requirements

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

Technologies

• ELT, ETL, SQL, Python, Spark
• Airflow, dbt
• AWS Glue, S3, Athena, IAM
• Redshift, Snowflake, BigQuery
• Lakehouse

Impact in the role

• 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, deliver one new dimensional model or semantic data product used by Marketing or business stakeholders for self-service analytics.
• Set up automated data quality monitoring on at least one production pipeline, including alerting for failures and anomalies.

Compensation and benefits

Pay: USD 75,000 - 85,000 per year.

• Restricted Stock Units (RSUs)
• Profit Share
• Medical, Prescription, Vision, and Dental insurance (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

Location

Pittsburgh, PA (onsite), with preferred commute area: Pittsburgh, PA 15220.